Journal articles on the topic 'Technical education Computer-assisted instruction Case studies'

Background Patient education delivered by a health care provider increases patients’ understanding and adherence to medical instructions, which helps to improve patient health. Multiple challenges exist to delivering effective patient education to patients with multiple chronic conditions, including giving the necessary time, range, and types of learning materials, and assessing the level of understanding. To help overcome these challenges, it is important to study new electronic means to assist in patient education, such as the use of mobile devices, interactive media, 3-dimensional images, and multimedia educational content at the bedside. Objective The goal of this study was to address the need for blended learning strategies combining technical and workflow integration of digital patient education systems for patients with chronic conditions within and across the regular process of care. Studies are needed to evaluate the utility and benefits of these technologies for providers and patients alike. Methods A mixed-methods approach was employed including survey administration to 178 patients after they received digital patient education in person with a health care provider, and qualitative interviews with 16 nurse educators who used the mobile digital health education technology to deliver instruction to patients. Patient survey data were analyzed using chi-square statistical tests. Qualitative interviews were analyzed for user acceptance and perceived value themes. Results Patients who were counseled using a blended digital health education approach reported improved understanding of educational content (P=.034) and chronic health conditions (P<.001), were more motivated to care for themselves at home (P<.001), were more likely to say that they felt capable of making health care decisions with their doctors (P<.001) and on their own (P=.001), and were more likely to report their intention to follow their doctor’s instructions (P<.001) than were patients whose education was not computer-based. Nurse educators felt that the digital education system and content enhanced their education efforts and could be easily integrated into the outpatient clinical workflow. Conclusions Patient education for individuals with chronic conditions may be more effective than traditional formats when provided in blended digital formats supervised by a health care provider.

The integration of technology in the classroom has become increasingly popular, with many educators seeing it as a way to enhance teaching and learning. However, there is a need to understand how technology is being used and how it is impacting both students and teachers. This qualitative study aimed to explore students' and teachers' perspectives on the use of technology in the classroom. Semi-structured interviews were conducted with eight teachers and ten students in a high school in the United States. The interviews were analysed using thematic analysis. The findings revealed that technology was perceived as a valuable tool for enhancing learning, but that there were also challenges associated with its use, such as technical difficulties and distractions. Additionally, students and teachers had differing opinions on how technology should be used in the classroom, with some students preferring a more traditional approach to learning. Overall, this study highlights the need for careful consideration of how technology is integrated into the classroom, as well as the importance of understanding students' and teachers' perspectives on its use. References Akbulut, Y., & Cardak, C. S. (2012). The advantages and challenges of using ICTs in teaching and learning processes: The case of a Turkish online university. The International Review of Research in Open and Distributed Learning, 13(2), 87-105. Al-Qudah, D. M., & Al-Dababneh, K. A. (2022). Investigating the impact of using educational technologies on English language teaching and learning at a higher education institution in Jordan. Education and Information Technologies, 27(1), 1-21. Alqurashi, E. (2021). The Impact of Mobile Learning on EFL Students’ Vocabulary Acquisition: A Meta-Analysis. International Journal of Emerging Technologies in Learning (iJET), 16(8), 36-54. Asif, M., Adil Pasha, M., Shafiq, S., & Craine, I. (2022). Economic Impacts of Post COVID-19. 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The adoption of methods and strategies validated through rigorous, experimentally oriented research is a core professional value of special education. We conducted a systematic review and meta-analysis examining the experimental literature on Technology-Aided Instruction and Intervention (TAII) using research identified as part of the National Autism Professional Development Project. We applied novel between-case effect size methods to the TAII single-case research base. In addition, we used meta-analytic methodologies to examine the methodological quality of the research, calculate average effect sizes to quantify the level of evidence for TAII, and compare effect sizes across single-case and group-based experimental research. Results identified one category of TAII—computer-assisted instruction—as an evidence-based practice across both single-case and group studies. The remaining two categories of TAII—augmentative and alternative communication and virtual reality—were not identified as evidence-based using What Works Clearinghouse summary ratings.

A review of: 
 Zhang, Li, Watson, Erin M. and Banfield, Laura. "The Efficacy of Computer-Assisted Instruction Versus Face-to-Face Instruction in Academic Libraries: A Systematic Review." The Journal of Academic Librarianship 33.4 (July 2007): 478-484.
 
 Objective – To conduct a systematic review of several studies comparing the efficacy of face-to-face versus computer-assisted instruction (CAI) for teaching basic library skills to patrons of academic libraries.
 
 Design – Systematic review of existing studies (randomised controlled trials and controlled trials). 
 
 Setting - College and university libraries 
 
 Subjects – The subjects studied were patrons of any type of academic library, whether university, college, or other post-secondary institution, receiving instruction in basic library skills. Ten studies were included in the review, of which seven were done in the United States, two in Australia, and one in Canada. The total number of subjects in all of the studies under review was 1283. Nine of the studies focused on undergraduates enrolled in specific courses (undergraduate courses ranging widely in subject area, or in one case a first year experience program); the other study focused on library instruction methods taught to students in a graduate research methods course, yet the study was still intended to measure the efficacy of library instruction methods, yet the study was still intended to measure the efficacy of library instruction methods. 
 
 Methods – One included study was a randomised controlled trial; the other nine were controlled trials. The date range under consideration was for studies done between 1990 and 2005. All original studies were required to compare the efficacy of face-to-face versus CAI instruction. Both information skills and students’ reactions to receiving the instruction were considered. To identify appropriate studies, searches were done across the following library and education-related databases: LISA, ERIC, and Library Literature. The authors screened the 728 unique studies’ bibliographic information for relevance against four criteria: studies had to be of a particular type of design (randomised controlled trials, controlled trials, cohort studies, and case studies), with a sample size greater than one and with pre- and post-test measurements; study participants had to be academic library patrons; the study needed to compare CAI and face-to-face instruction; and both the students’ information skills and reactions to the instruction had to be measured. This left 40 unique studies, which were then retrieved in full text. Next, studies were selected to meet the inclusion criteria further using the QUOROM format, a reporting structure used for improving the quality of reports of meta-analyses of randomised trials (Moher, David et al 1896 - 1900). Evaluation of methodological quality was then done using a dual method: authors Watson and Zhang assessed the studies independently, each using the “Checklist for Study Quality” developed by Downs and Black (Downs, Sara H. and Black, Nick 377-384), adapted slightly to remove non-relevant questions. After analysis, when additional information was needed, original study authors were contacted. Finally, ten studies were included in the analysis. 
 
 The instruction sessions covered many topics, such as catalog use, reading citations, awareness of library services and collections, basic searching of bibliographic databases, and more. But all could qualify as basic, rather than advanced, library instruction. All studies did pre- and post-tests of students’ skills – some immediately after instruction, and others with a time lapse of up to six weeks. Most authors created their own tests, though one adapted an existing scale. Individual performance improvement was not studied in many cases due to privacy concerns. 
 
 Main Results - Nine of the ten studies found CAI and face-to-face instruction equally effective; the tenth study found face-to-face instruction more effective. The students’ reaction to instruction methods varied – some students felt more satisfied with face-to-face instruction and felt that they learned better, while other studies found that students receiving CAI felt more confident. Some found no difference in confidence. 
 
 It was impossible to carry out a meta-analysis of the studies, as the skills taught, methods used, and evaluation tools in each case varied widely, and the data provided by the ten studies lacked sufficient detail to allow meta-analysis. As well, there were major methodological differences in the studies – some studies allowed participants the opportunities for hands-on practice; others did not. The CAI tutorials also varied – some were clearly interactive, and in other studies, it was not certain that the tutorial allowed for interactivity. 
 
 The authors of the systematic review identified possible problems with the selected studies as well. All studies were evaluated according to four criteria on the modified Downs-Black scale: reporting, external validity, and two measures of internal validity (possible bias and possible confounding). A perfect score would have been 25; the mean score was 17.3. Areas where authors lost points included areas such as failure to estimate data variability, failure to report participants lost to follow-up, failure to have blind marking of pre- and post-tests, failure to allocate participants randomly, and a variety of other areas. As well, few studies examined participants’ confidence level with computers before they participated in instruction.
 
 Conclusion – Based on this systematic review, CAI and face-to-face instruction appear to be equally effective in teaching students basic library skills. The authors of the study are reluctant to state this categorically, and issue several caveats: a) only one trial was randomised; b) seven of the studies were conducted in the USA, with the others being from Canada and Australia, and learning and teaching styles could be very different in other countries; c) the students were largely undergraduates, and the authors are curious as to whether results would be similar with faculty, staff, or older groups (though of course, not all undergraduates are traditional undergraduates); d) the tests ranged widely in design, and were largely developed individually, and the authors recommend developing a validated test; and e) if the pre- and post-tests are identical and given in rapid succession, this could skew results.

Students of Elementary School Teacher Education programs must be able to have higher-order thinking skills (HOTS) so that they can train students to have HOTS through learning activities created when they have become elementary school teachers. This study aims to explain students' high-level thinking skills in solving HOTS-oriented questions in Instructional Evaluation courses. This study uses qualitative research methods with data collection techniques using cognitive test instruments in the form of descriptions. Data analysis techniques use simple descriptive statistics. The results showed the level of thinking ability of students in answering HOTS practice questions still needed improvement. Students who have high learning abilities are better at answering HOTS-oriented questions compared to students in the medium and low categories. Recommendations for future research are required learning modules that can facilitate learning activities that lead to HOTS so that students are skilled in answering and making HOTS-oriented practice questions for elementary school students when they become a teacher.
 
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With the deepening of information technology and ongoing higher education reforms in China, the course Computer Organization Principles faces challenges such as abstract content, a disconnect between theory and practice, and difficulty integrating ideological and political education. To address these issues, this study develops a hybrid instructional model that integrates both online and offline components, combining the BOPPPS teaching framework with blended learning strategies. In the pre-class phase, clearly defined learning objectives and diagnostic pre-assessments are delivered online to stimulate autonomous learning; during class, contextualized case studies and collaborative group activities support participatory learning; in the post-class phase, laboratory reports and reflective summaries close the loop between knowledge and values. A diversified evaluation system ensures fairness and comprehensiveness, offering valuable insights for the ongoing improvement and refinement of the teaching model. Empirical results from a controlled experiment with two cohorts demonstrate that this blended model not only enhances students' technical competencies but also effectively cultivates their values, indicating strong potential for broader implementation.

<em>The study adopted survey and correlational design to determine appropriate method for teaching&nbsp;&nbsp; Entrepreneurship education in Federal College of Education (Technical) Bichi, Kano State. The study assessed the students&rsquo; attitude/mind-set and appropriate methodology for teaching entrepreneurial education. The population comprises of 86 lecturers purposively selected and 50 students with ten (10) each randomly selected from five (5) schools. The instrument for data collection was a questionnaires design to elicit information on attitude and methodologies from students and lecturers respectively and pre-test and post-test administered before and after treatment of both control and experimental group with conventional and activity-based teaching methods. The instrument was validated by two research experts. The reliability coefficient of 0.75 was obtained through a Cronbach Alpha analysis of the copies of the instrument used for pilot testing. Frequency count, simple percentage and t-test were the statistical tools used for data analysis. Findings revealed among others that some students are positive on their perspective on the need for entrepreneurship education, teaching methods such as simulation, case study computer assisted instruction and activity-based methods among others identified as suitable for teaching entrepreneurial education. The results of the hypothesis tested revealed that majority of the students&rsquo; scores increased in experimental group as compared to the control group indicating that participants from experimental group showed more achievement in post-test with higher mean scores than those in the control group. Based on the findings, it was recommended among others that priority should be given to the use of activity-based method while teaching Entrepreneurship education at all level in Colleges of Education.</em>

During the past five years, with support from the RCPSC, a collaborative group of researchers conducted projects investigating issues related to simulation based training of technical surgical skills. The aim of this presentation is to review the body of work generated, its significance, and outline future research plans. &#x0D; In all studies, participants were medical students and residents from 3 medical schools in Ontario. First, we successfully demonstrated that trainees benefit from simulation-based practice by improving their ability to multitask. This ability not only increases technical proficiency, but also results in an enhanced ability to learn other aspects of surgery. Second, we showed that the adaptation of learning theories helps in optimizing training curricula by matching the fidelity of a simulator to the trainees’ level of expertise. Third, we provided validation of both expert and computer based methods for assessment. We showed that computer based assessments are sufficient for the evaluation of trainees learning fundamental skills, while expert based measures are more effective in the evaluation of performance on complex technical skills. Finally we demonstrated that examination-induced stress has a facilitating effect on trainees’ skills performance. &#x0D; This body of research lends support for the inclusion of a simulation based approach to training technical skills. It also highlights the importance of the choice of assessment methods. Collectively this work highlights the need for further research in the optimization of training methods by the incorporation of learning theory into the existing training curricula. Related to this, further research in our laboratory will investigate the effects of practice schedule and expert feedback, as well as the role of self-regulated practice in the acquisition of technical surgical skills.&#x0D; Xeroulis GJ, Park J, Moulton CA, Reznick RK, Leblanc V, Dubrowski A. Teaching suturing and knot-tying skills to medical students: a randomized controlled study comparing computer-based video instruction and (concurrent and summary) expert feedback. Surgery 2007; 141(4):442-9. &#x0D; Brydges R, Sidhu R, Park J, Dubrowski A. Construct validity of computer-assisted assessment: quantification of movement processes during a vascular anastomosis on a live porcine model. Am J Surg. 2007; 193(4):523-9. &#x0D; Brydges R, Carnahan H, Backstein D, Dubrowski A. Application of motor learning principles to complex surgical tasks: searching for the optimal practice schedule. J Mot Behav. 2007; 39(1):40-8.

This paper addresses the need for a positive and effective learning environment for engineering students in non-computer science fields to grasp Generative AI principles while navigating the intricate balance between its application and developmental insights. Drawing from pedagogical theories and cognitive science, especially Leinenbach and Corey (2004)’s Universal Design for Learning, this study proposes a framework tailored to the unique needs and backgrounds of engineering students. The framework emphasizes active learning strategies, collaborative problem-solving, and real-world applications to engage learners in meaningful experiences with Generative AI concepts. The central learning context is a M.Sc. program in management engineering with a course/training opportunity in Machine Learning Fundamentals using Python based on Google Collab. The introduction of Generative AI is based on selected Google libraries for Python. Furthermore, this paper explores various instructional approaches and tools to scaffold students' understanding of Generative AI, including hands-on projects, case studies, and interactive simulations. It also addresses ethical considerations and societal implications associated with Generative AI deployment, encouraging students to critically reflect on the broader impacts of their technical decisions. Through a synthesis of pedagogical best practices and AI development principles, this paper contributes to the ongoing discourse on effective AI education for non-computer science disciplines. By embracing a holistic approach that integrates theory with practical application, educators can empower engineering students to harness the transformative potential of Generative AI while navigating its complexities responsibly and ethically.

This study aims to find empirical information about the effect of Technological Pedagogical Content Knowledge (TPACK), and Technology Integration Self Efficacy (TISE) on Teacher Readiness for Online Learning (TROL). This study uses a quantitative survey method with path analysis techniques. This study measures the readiness of kindergarten teachers in distance learning in Tanah Datar Regency, West Sumatra Province, Indonesia with a sampling technique using simple random sampling involving 105 teachers. Empirical findings reveal that; 1) there is a direct positive effect of Technology Integration Self Efficacy on Teacher Readiness for Online Learning; 2) there is a direct positive effect of PACK on Teacher Readiness for Online Learning; 3) there is a direct positive effect of Technology Integration Self Efficacy on TPACK. If want to improve teacher readiness for online learning, Technological Pedagogical Content Knowledge (TPACK) must be improved by paying attention to Technology Integration Self Efficacy (TISE).&#x0D; Keywords: TROL, TPACK, TISE, Early Childhood Education&#x0D; References:&#x0D; Abbitt, J. T. (2011). An Investigation of the Relationship between Self-Efficacy Beliefs about Technology Integration and Technological Pedagogical Content Knowledge (TPACK) among Preservice Teachers. Journal of Digital Learning in Teacher Education, 27(4), 134–143.&#x0D; Adedoyin, O. B., &amp; Soykan, E. (2020). Covid-19 pandemic and online learning: The challenges and opportunities. Interactive Learning Environments, 1–13. https://doi.org/10.1080/10494820.2020.1813180&#x0D; Adnan, M. (2020). Online learning amid the COVID-19 pandemic: Students perspectives. Journal of Pedagogical Sociology and Psychology, 1(2), 45–51. https://doi.org/10.33902/JPSP.2020261309&#x0D; Alqurashi, E. (2016). 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Nursing is an applied profession which requires the combination of theoretical content and practical skills in a meaningful way. Nursing education must help students internalize information, skills, attitudes, professional values and ethical standards concerning the discipline and make them a part of their behavior. Nursing education necessitates an education system which covers all cognitive, affective and psychomotor areas of learning at a level of adequacy that could get students to assume the specified roles. As well as technical skills, such skills as providing a holistic and empathic health care and communication and team cooperation must be included by this system. The main objective of nursing education is to train nurses who can combine theory and practice, think critically in the learning process and have acquired effective problem solving skills. In the educational settings of our day, different teaching technologies are employed at each stage of instruction. Many instructional methods and strategies are tried out for the improvement of information and skills in nursing education. A great majority of educational methods and strategies consists of computer aided education, simulation and distance education approaches. One of the methods employed in order for students to improve their competence in health care management and to gain perfection. It is not always possible for students to gain appropriate clinical experience because they spend less time in the clinic due to such reasons as the limited areas of clinical practice in the complex structure of health care system, shorter stays of patients in hospitals and problems concerning the education system. However, despite all these negative factors, nurses are expected to possess the ability to perform nursing skills perfectly when encountered challenging situations. Considering such restrictions, simulation based learning plays a pivotal role for nursing students studying in the constantly changing health care system to get properly prepared.Simulation practices are considered as a significant step towards offering safe care to patients in health care services by providing a learning environment in which environmental risks are minimized. In recent years, patient stimulators that have high fidelity have attracted gradually increasing interest as en educational tool in nursing education. This review was planned with the aim of examining the results of studies carried out on the use of high fidelity simulation in nursing education. Study population consisted of 53 published studies which were reached as a result of the review of the data bases, “Pubmed” and “Science Direct” using the keywords “simulation”, “nursing”, “education”, “students” and “high fidelity” in April-May 2017. In the review, articles which were published in English and had their full texts were chosen for examinations. 23 studies meeting the criteria of the present research comprised the study sample. More than half the studies (15) included in the review cover the comparison of high fidelity simulation with another learning method. High fidelity simulation is also seen to be compared with standardized patients, traditional learning methods and moderate and low fidelity simulation. In the examination of the results of these studies most methods showed no superiority to others, but it was found that knowledge, skills and performance scores increased in the education offered using high fidelity simulation. In conclusion, in the education carried out with high fidelity simulation, increases can be observed in students’ clinical thinking and decision making, confidence, motivation and motor skills. Therefore, the use of simulation in the education of nursing students is accepted as the golden standard.Extended English abstract is in the end of PDF (TURKISH) file.ÖzetHemşirelik, kuramsal içeriğin, pratik beceri ile anlamlı bir biçimde birleşmesini gerektiren uygulamalı bir meslektir. Hemşirelik eğitimi; öğrencilere belirtilen rolleri kazandıracak yeterlilikte bilişsel, duyusal ve psikomotor öğrenme alanlarını kapsayan bir eğitim sistemini gerektirmektedir. Bu sistemde teknik becerilerin yanı sıra; bütüncül ve empatik bakım verme, iletişim ve ekip işbirliği gibi beceriler de yer almalıdır. Hemşirelik eğitiminde temel amaç; teori ile uygulamayı birleştirebilen, öğrenme sürecinde eleştirel düşünebilen ve etkin problem çözme becerisi kazanmış hemşireler yetiştirmektir. Günümüzde eğitim ortamlarında, öğretim sürecinin her aşamasında farklı öğretim teknolojileri kullanılmaktadır. Eğitim yöntem ve stratejilerinin önemli bir grubunu, bilgisayar destekli eğitim, simülasyon ve uzaktan eğitim yaklaşımları oluşturmaktadır. Öğrencilerin hasta bakım yönetiminde yeterliliğini geliştirmesi ve yetkinlik kazanması için benimsenen yöntemlerinden birisi de simülasyondur. Sağlık bakım sisteminin karmaşık yapısı içinde klinik uygulama alanlarının sınırlı olması, hastaların hastanede kalış sürelerinin kısalması ve eğitim sistemi kaynaklı nedenlerle klinikte daha az zaman geçirmeleri sonucunda öğrencilerin uygun klinik deneyim kazanabilmeleri her zaman mümkün olamamaktadır. Ancak tüm bu olumsuz faktörlere rağmen hemşirelerden zor durumlar karşısında hemşirelik becerilerini eksiksiz sergileyebilecek yeteneğe sahip olmaları beklenmektedir. Söz konusu sınırlamalar göz önüne alındığında, simülasyon temelli öğrenme, sürekli değişen sağlık bakım sistemi içinde eğitim gören hemşirelik öğrencilerinin yeterli hazırlanmasında anahtar rol oynamaktadır.Son yıllarda gerçekliğe yakınlığı yüksek hasta simülatörleri hemşirelik eğitiminde bir eğitim aracı olarak giderek artan bir ilgiyle kullanılmaktadır. Bu derleme hemşirelik eğitiminde yüksek gerçeklikli simülasyon kullanımına yönelik yapılan çalışmaların sonuçlarını incelemek amacıyla planlanmıştır. Çalışmanın evrenini Nisan-Mayıs 2017 tarihlerinde “simülation”, “nursing”, “education”, “students”, “high fidelity” anahtar kelimeleriyle, “Pubmed” ve “Science Direct” veri tabanları taranarak yayınlanmış olan 53 çalışma oluşturmuştur. İncelemede, yayın dili İngilizce olan ve tam metni bulunan makaleler seçilmiştir. Araştırma kriterlerini karşılayan 23 çalışma derlemenin örneklemini oluşturmuştur. Derlemeye dahil edilen araştırmaların yarısından fazlası (15) yüksek gerçeklikli simülasyon ile bir diğer öğrenme yönteminin karşılatırılmasından oluşmaktadır. Yüksek gerçeklikli simülasyonun; standardize hasta, geleneksel öğrenme yöntemleri, orta ve düşük gerçeklikli simülasyon ile karşılaştırıldığı görülmektedir. Bu çalışmaların sonuçları incelendiğinde çoğunun birbirine karşı bir üstünlüğü bulunmamış fakat yüksek gerçeklikli simülasyon ile yapılan eğitimde bilgi, beceri ve performans puanlarında artma olduğu saptanmıştır. Sonuç olarak yüksek gerçeklikli simülasyon ile yapılan eğitimde; öğrencilerin klinik düşünme ve karar verme, özgüven, motivasyon ve motor becerilerinde artma görülmektedir. Bu nedenle, hemşirelik öğrencilerinin eğitiminde simülasyon kullanımı altın standart olarak kabul edilmektedir.

&#x0D; &#x0D; &#x0D; One form of early mathematical recognition is to introduce the concept of geometric shapes. Geometry is an important scientific discipline for present and future life by developing various ways that fit 21st century skills. This study aims to overcome the problem of early mathematical recognition of early childhood on geometry, especially how to recognize geometric forms based on computer learning. A total of 24 children aged 4-5 years in kindergarten has to carrying out 2 research cycles with a total of 5 meetings. Treatment activities in each learning cycle include mentioning, grouping and imitating geometric shapes. There were only 7 children who were able to recognize the geometric shapes in the pre-research cycle (29.2%). An increase in the number of children who are able to do activities well in each research cycle includes: 1) The activities mentioned in the first cycle and 75% in the second cycle; 2) Classifying activities in the first cycle were 37.5% and 75% in the second cycle; 3) Imitation activities in the first cycle 54.2% and 79.2% in the second cycle. The results of data acquisition show that computer learning application can improve the ability to recognize geometric shapes, this is because computer learning provides software that has activities to recognize geometric shapes with the animation and visuals displayed.&#x0D; Keywords: Early Childhood Computer Learning, Geometry Forms, Early Math Skills&#x0D; Reference&#x0D; &#x0D; &#x0D; &#x0D; Alia, T., &amp; Irwansyah. (2018). Pendampingan Orang Tua pada Anak Usia Dini dalam Penggunaan Teknologi Digital. 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Objectives: To assess the evidence of information communication technology (ICT) use in the training of maternal and child health (MCH) workers, discuss methodological issues present in the identified studies, and identify future work areas. Introduction: The explosive growth of cellphone usage in low and middle-income countries (LMIC) has made mobile technology an increasingly attractive form of information communication technology (ICT) to be used to meet healthcare needs that go unmet, rising due to the paucity of trained clinical workers (O’Donovan, Bersin, &amp; O’Donovan, 2015). The portability and relative low cost of cellphones have made them ubiquitous and efficient to use. For example, subscriptions in Africa have risen from 12.4 per hundred inhabitants in 2005 to per hundred inhabitants in 2015 (ITU, 2017). ICT is an umbrella term that encompasses the hardware, software and networks that provide its users with data and information resources. As far as healthcare is concerned, these resources include access to varied tools and services such as electronic health records, point-of-care databases, decision support systems, clinical guidelines or training modules for continuing education (Machingura et al., 2014). This technology has made healthcare more efficient in affluent countries where funding and infrastructure to build, support and maintain ICT is readily available. However, ICT development is critical to LMIC’s which have the greatest barriers to effective and efficient healthcare systems and fewer resources to overcome challenges. The aims of this paper are to (1) summarize the literature on ICT use in the training of MCH workers, (2) discuss methodological issues present in the identified studies, and (3) identify future work areas. Our specific research questions are: Which ICT tools have been used in developing countries for training the MCH workforce? How successful are the tools for instructing health care workers? A major impediment to health care improvements in underdeveloped countries is the low ratio of health professionals to patients. A developed workforce is critical for sustaining healthcare infrastructure. Because there is an insufficient number of professional practitioners, many MCH health needs are met by community workers with limited or no formal training (Chipps et al., 2015). Since the level of services range from general check-ups to life-saving interventions, training must address a variety of educational requirements. (Agarwal et al., 2015). In addition to primary professional education, health workers require training for re-licensure and continuous professional development (CPD). Training, particularly in remote areas, requires travel, time away from work as well as funding for food and lodging (Chipps et al., 2015). This exacerbates uneven healthcare coverage with the majority of MCH health care workers concentrated in urban centers, leaving rural residents with inadequate services (Middleberg et al., 2013; Modi et al., 2015). ICT reduces costs by enabling personnel to remain in their communities while providing digital access to educational content, mentors, guidelines and decision support systems (Saronga et al., 2015). It is commonly recognized that underdeveloped countries have occasional brown-outs in their urban centers and the power grid may not reach rural or remote areas. Even if seed money is acquired for start-up costs, funding for technology maintenance and technical manpower beyond the pilot stage can be tentative (Achampong, 2012). Secondly, while cell phone use across LMICs has exploded in recent years, its use for advancing training has not grown in comparison. A limited number of reports have been published, reporting the use of ICT for communication (Andreatta et al., 2011), tracking health worker behavior (Awoonor-Williams et al., 2013), attitudes towards using ICT (Sukums et al., 2014; Zakane et al., 2014), and the impact of the design of ICT (Valez et. al., 2014). This paucity of studies understanding the impact of ICT on measurable training outcomes leaves a troubling gap in the literature if progress is to be made in addressing the training needs. Finally, government entities, educators and administrators may be reluctant to adopt ICT into health training for practical, fiscal and political reasons. Because health personnel may not have exposure to technology in their daily lives, staff may require basic computer training on operating systems, file management, word processing and databases in conjunction with ICT projects (Sukums, 2014). In addition to a lack of knowledge about computers in general, use of ICT also comes with associated monetary costs. Both of these issues are also exacerbated by resulting government policy changes. We endeavored to fill this gap by completing a literature review to bring the disparate work together, but to our surprise, it did not really exist. This paper reports on (1) what studies have been conducted on the use of ICT in training; (2) what common methods are used and how they are evaluated and (3) what outcomes have been reported. Methods: Medline (OVID), CINAHL and Web of Science were searched for relevant articles published between January 1, 2007 and February 28, 2017. Studies were included if they included training and education in low and middle-income countries using ICT for maternal child health workers. Results: 111 unique articles from electronic searches with seven additional articles discovered through hand-searching reference lists were identified. After review, 15 articles aligned with the necessities to analyze the current environment of the ICT tools. The study designs in the reviewed articles were usually pre- and post-evaluations (n=7). There were also a small number of single cross-sectional studies (n=3) measuring the use of the tool. Two studies also evaluated the use of electronic clinical decision support systems (CDSS) applications or algorithms. The remainder of the studies (n=3) used ICT to provide resources for meeting information needs, as well as repositories of protocols and best practice documents. The outcomes reported ranged from access to medical resources (n=3), accuracy in clinical documentation (n=2), need for remedial computer training (n=2) and an increase in clinical knowledge and proper use of protocols (n=4) Discussion and conclusion: The current evidence-base does not show a clear indication that there were particular initiatives using ICT for the training of health workers. While the majority of projects identified were shown to improve outcomes, there were limited results reported. This lack of documented evidence hinders decisions about the content and methods that should be used to support training. We are missing an opportunity for advancement. The World Health Organization identified community health worker training as a lever to move the improvement of health care in low and middle-income countries (LMICs). An understanding of barriers and facilitators to using ICTs to meet this need, provides key directions for policy makers and non-governmental organizations as they apply limited resources to these issues.

The introduction of basic computer media for early childhood is very important because it is one of the skills that children need in this century. Need to support parents and teachers in developing the implementation of the use of computer technology at home or at school. This study aims to determine and understand the state of learning conducted based on technology. This research uses a qualitative approach with a case study model. This study involved 15 children and 5 parents. Data obtained through interviews (children and parents) and questionnaires for parents. The results showed that children who were introduced to and taught basic computers earlier became more skilled in learning activities. 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To improve online learning pedagogy within the field of paralegal education, this study investigated how paralegal students and paralegal instructors perceived the effectiveness of synchronous and asynchronous online paralegal courses. This study intended to inform paralegal instructors and course developers how to better design, deliver, and evaluate effective online course instruction in the field of paralegal studies.Survey results were analyzed using independent samples t-test and correlational analysis, and indicated that overall, paralegal students and paralegal instructors positively perceived synchronous and asynchronous online paralegal courses. Paralegal instructors reported statistically significant higher perceptions than paralegal students: (1) of instructional design and course content in synchronous online paralegal courses; and (2) of technical assistance, communication, and course content in asynchronous online paralegal courses. Instructors also reported higher perceptions of the effectiveness of universal design, online instructional design, and course content in synchronous online paralegal courses than in asynchronous online paralegal courses. Paralegal students reported higher perceptions of asynchronous online paralegal course effectiveness regarding universal design than paralegal instructors. No statistically significant differences existed between paralegal students’ perceptions of the effectiveness of synchronous and asynchronous online paralegal courses. A strong, negative relationship existed between paralegal students’ age and their perceptions of effective synchronous paralegal courses, which were statistically and practically significant. Lastly, this study provided practical applicability and opportunities for future research. Akyol, Z., &amp; Garrison, D. R. (2008). 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The world of robotics has long been trying to teach the essence of engineering by using robots as a subject. A process of robot production and operation is said to have the total essence of engineering education, and the actual manufacturing of robots has certainly been motivational for students. For this reason, robotics researchers and those in educational institutions such as universities and technical colleges in particular have worked hard on robot education. However, researchers have been faced with a dilemma: a report of educational activities, however, has not been regarded as a research paper, even though they have worked so hard on it. This special issue intends to resolve the dilemma and convey their educational activities in educational literature. From a scientific point of view, we will utilize robots in robot education to activate human resource development in robotics in terms of both quantity and quality. Learning sciences researchers focus on what educational content they want to give and get back through various learning processes that enable such education. More specifically, they analyze what activities in what educational contexts yield what effects to what extent, thereby facilitating learning of higher quality than ever. The same attempt may be possible for education using robots. Various practices that give us hope for good results have been conducted independently. Comparison of those practices may result in the extraction of a principle to bring about learning of higher quality. A single report itself on a practice is not likely to be a research paper. Instead, in an effort to promote robotics itself, a compilation of processes and results of various educational attempts with various clear and specific subgoals that are comparable and examinable can be a precious group of research papers from which principles of attempts in engineering education are drawn. The formation of a community in which practices are conducted, processes and results are shared, and further practices are planned is highly likely to improve the overall quality of practices. This special issue provides the first step towards such formation of a new community based on such a compilation of new research. Educational research papers, common assets for the formation of such community, are thus required to clearly include the following contents which constitute an education literature. • Purpose of learning: Learners with what background knowledge acquire what and to what extent. • Activity program: The purpose of learning is achieved specifically through what activities, in what order, implemented for what period of time. • Learning process: During the course of the program, what specific learning activities are observed. • Assessments: Whether expected activities are made, to what extent the purpose is achieved, and whether activities and results seen are beyond what was expected. If at least the above items come to be known from one practice, subsequent practices can be improved and new goals can be set. At the same time, the practices can be observed on other occasions. Once an original “learning score,” like a musical score, is manifested, it will be able to be improved or edited. As no two musical performances are the same as a written musical score, no two practices will be the same as one “learning score.” However, that does not mean that the “learning scores” and their processes in practice are not subjects of research. As musical scores and performances are studied for the next composition and more impressive performance, “learning scores” and their outcomes in practice are the subjects of research aimed at designing better future processes and conducting practices of higher quality. The attempts in this special issue are expected to inspire more and more elaborative papers and to improve the quality of practices that utilize the results. This time, the first time, we had as many as 39 contributions from the public. We asked referees to select those that would constitute as diverse a collection as possible, and they finally adopted 29 contributions. We are sure that with these contributions as our point of departure, the accumulation of results will continuously engender next-dimension practices in the future. Let us now overview the papers selected this time and discuss their findings for the future contributions in three areas: purpose, contrast, and assessment. Please forgive us if the discussions overlap to some extent, but they include factors that are more related than independent. &lt; Contrast in Purpose and Result &gt; Goal setting is normally difficult in educational research. As a result, the most common mistake is that goals are set that are overly ambitious. The fact the goal of compulsory education currently set by the Ministry of Education, Culture, Sports, Science and Technology is a “zest for living” serves to indicate that the idea “the bigger the educational goal, the better” prevails. Big goals cannot be accomplished at once, however, so clearer and more specific interim goals of half-year, one-year, and four-year duration need to be set. To link the subject of research to the next practice, we have to specify as clearly as possible what interim activities and what results we expect. Otherwise, we will have vague results which do not merit papers. An example of a real story to show what a specific goal is like is warranted here. A researcher teaching biology in a liberal arts course, in the final examination after all the lectures, tasked his students with the following: “name, in their order of importance, technical terms that you had not intended to remember but actually did during the course, and explain their definitions in that order in the time allotted.” The task may seem far-fetched, but he actually expected a certain list of terms and their explanations. He had in fact intended for the students to be able to reproduce the terms on the list and be able to explain them; he had explained them by introducing the terms in a well-prepared order, using them repeatedly, encouraging the students to use them, and setting an opportunity for the students to explain them among themselves. Such effort made this practice popular among the students and made the task performance exceed his expectations. This practice program and the report of its process could be of very high quality as subjects of research. We can carefully track which of the planned activities facilitated learning, how active they were, and what level of results were brought for each term. If the students’ answers include important items that the students learned spontaneously although the teacher did not mean to teach them to that extent, this practice clearly “produced higher results than expected.” If we can review the records of the learning process (e.g., videos of the classes, records of the students’ conversations, copies of notes taken by the students in each lecture, etc.), we can at least guess which of the activities at what point in time produced the more-than-expected results, and we can produce a specific plan for the next practice. Thus, it is very beneficial to specify the educational goals before working on practices. &lt; Contrast &gt; Learning sciences are asking less and less for socalled “control groups” for their research. This is because, for the betterment of the next practice, it is more efficient to use the time for reviewing the process of a successful practice than making a single factor comparison, because what we want to know is not whether it worked but how it worked in relation with other factors. There are many reasons a practice gives the desired results or not, and they interact. Therefore, even if a cause or contributing factor to a successful outcome is identified, it can not be the only factor behind its success. This does not mean, however, that educational research should not compare at all, rather than that, if there are two or more paths to the successful accomplishment of a specific goal, comparing of them allows factors associated with the results to be identified more easily. In that sense, when devising a new way of teaching, it is often meaningful to compare both the processes and results of the first practice and second practice with slightly adjusted approach based on the results of the first practice. Regarding education using robots, there is an idea that the tangible nature of robots has educational effects on students through their physical experiences that can not be expected from classroom lectures alone. Here is an imaginary example. Suppose that a class previously allowed students to deal with an object only on a computer screen, but now the students are provided with a real model. Now suppose this real model has had some effects, but not to the level expected. In the second year, the class again includes operations on the screen in its introductory period, and, after the students have discussed the robot’s operation, a hands-on experience is provided. As a result, the second practice has almost the expected results despite the fact that the discussion on the operation on the screen has reduced the time for the operation of the real object. Now, how can this result be documented in a paper? In other words, how can this practice be reported in such a way that the reporter and readers may develop the next practice? A conclusion that “a hands-on experience may be important but the length of time does not affect the results” does not focus on what class is to be devised next. First of all, such conclusion misses the point in terms of the successful experience the second time. Now suppose that this practice is video-recorded at a level of resolution high enough to allow the comparison of the processes of the first and second classes. Reviewing the progression of the first class, we find that the model is introduced too early for the students to understand how to operate the real object and time is wasted over it. For this reason, the students utilize only about two-thirds of the expected length of time assigned to operation of the real object. Reviewing the progression of the second practice, we find that the length of time for discussion of the screen operation is just about one-third of the length of time assigned to the real object operation in the first class; that is, the length of time to operate the real object that is thought to be reduced is almost the same as that utilized in the first class. The first and the second classes are compared as Table 1. Although it may seem to be an afterthought, the results of the comparison of the two practices will be concluded as “to effectively learn from the actual object operation, the balance between the length of time to clarify what to do in the actual object operation and then the length of time to actually operate the object is apparently more important than the total length of time assigned to the actual object operation.” Some of the papers adopted this time should have manifested such comparison for an easier-to-understand result. &lt; Assessment &gt; Assessing what was learned as a result of teaching is more difficult than normally thought. Suppose we ask students the question, “In what year was Natsume Soseki (a Japanese famous novelist) born?” Which of the students should we give a higher score: a student who answers “1867” correctly, or a student who answers, “In the middle of the 19th century, probably,” based on the year of the Meiji Restoration, the year of the outbreak of the Thirty Year’sWar, and other betterknown years? In this case, the latter student often has more historical perspective than does the former. Tests require various problem-solving processes, depending on the way the questions are posed (or one’s understanding of what was asked). In that sense, an assessment is defined as “an interpretation of a cognitive process that, from a behavior observed by an approach, leads to the behavior.” The “approach” here is the equivalent of the test question above (i.e., the action of asking the year of Soseki’s birth), and “the behavior observed” is the equivalent of the answer of each student. The essence of an assessment depends on what the cognitive process that drew the answer interpreted from the behavior is. In this case, the answers of the two students imply that the cognitive process of the former student may only be to refer to a chronological table; on the other hand, that of the latter may be closer to a process of making an inference from a series of relevant events structured in memory as modern history. If one needs to confirm whether such interpretation is true, the student can be asked to elaborate in the assessment, i.e., the student can be asked a couple of similar questions, and the overall tendency of his observable behaviors may be interpreted. This suggests educational research consisting of continuous assessments rather than of a single collective assessment. In fact, the former involves elaboration but gives stable interpretations. Scoring the students by their performance over a couple of weeks of practice totaling several hours, performance that allows their behaviors to be observed, based on a confident, down-to-earth grade, is easier than scoring the students by their performance in once-a-week classes in a large lecture hall where individual reactions are invisible to the teacher and assessment is based only on the result of a single examination. Accordingly, if a practice is the subject of research, its results do not have to depend only on the final, single examination. Also, relying on a subjective assessment, which is more difficult to interpret, is not necessarily a wise thing to do. A stable assessment is achieved by continuously providing opportunities for behavioral observations in which cognitive processes are easy to interpret. Practices utilizing robots givemore opportunities for student observation for the purpose of assessment than other classes (e.g., mathematics or philosophy) in the sense that the students “externalize what they think” with a real subject. Educational research on robot education should take advantage of this. This argument can be countered by an argument that it is impossible to analyze such a great amount of data on the learning process, such as video. One of the answers to this counterargument is that it is good to keep as much data as possible to, when necessary, analyze it as needed. Now we look back the example of the imaginary classroom of experiential learning that we saw when we discussed the comparison. When we interpret the results of the two practices, if the length of time for actual object operation is focused on, we may first measure only the point in question from the video. Simply doing so ends up the discussion in the above example. Although time cannot be measured without a video record, measuring time is sufficient for one to be able to write a paper in the above example. In that sense, data on a leaning process is worth recording. In addition, if a further hypothesis, i.e., there is a difference in results depending not only the length of time but also how to use the time by each team between a group that performed a specific actual object operation and a group did not perform it, is generated, the video may be viewed again, and the occurrence of the specific activity alone can be focused on as a subject of analysis. Adding a report of learning process analysis results led by such a hypothesis not only facilitates the practice results to be brought into a paper but also serves as a strong factor that may lead to the next practice, the next educational study, and the next paper. Those researchers who have been involved in engineering education utilizing robots may each have individual hypotheses for better ways of teaching from their own individual experiences. Clarifying the instructional goal itself is the subject of research. By being aware of a hypothesis, translating a “better way of teaching” into reality in line with the hypothesis, clarifying an instructional goal, determining from a series of learning processes to what extent the goal can actually be accomplished, and reporting all of them to leave them to cooperative examination, those rules of thumb can be turned into learning principles. This special issue is, in that sense, the first step to new learning research.

Amidst the ever-changing landscape of English language education, where virtual platforms shape new learning paradigms, this research determines the revolutionary potential of ChatGPT to foster English language acquisition in Pakistan. English is a second language in Pakistan and the learners face multiple challenges in its acquisition. To understand the influence of ChatGPT on English language students, the study relied on quantitative data, using the Technology Acceptance Model (TAM) along with social impact. To test the hypothesized relationships, the study gathered 400 valid responses from English-language students studying at various universities in the southern districts of Khyber Pakhtunkhwa province via purposive sampling. For data analysis, the study applied structure equation modelling through Smart-PLS and found that social influence, perceived usefulness, and perceived ease of use stimulate students’ intentions to use ChatGPT for English language learning. The research fills the gap between English language learners and technology usage, which helps to better understand the connection between AI-based platforms and English learning. This study is helpful for teachers, students, and tech firms to focus on solving students’ learning problems through AI tools. References: Abramson, A. (2023). How to use ChatGPT as a learning tool. Monitor on Psychology, 54(3). Ajzen, I., &amp; Fishbein, M. (1972). Attitudes and normative beliefs as factors influencing behavioural intentions. Journal of personality and social psychology, 21(1), 1. Alfadda, H. A., &amp; Mahdi, H. S. (2021). Measuring students’ use of Zoom application in language course based on the technology acceptance model (TAM). Journal of Psycholinguistic Research, 50(4), 883-900. Almogren, A. S., Al-Rahmi, W. M., &amp; Dahri, N. A. (2024). Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective. Heliyon. Almusharraf, A., &amp; Bailey, D. (2023). Predicting attitude, use, and future intentions with translation websites through the TAM framework: a multicultural study among Saudi and South Korean language learners. Computer Assisted Language Learning, 1-28. Alzoubi, H. (2024). Factors affecting ChatGPT use in education employing TAM: A Jordanian universities’ perspective. International Journal of Data and Network Science, 8(3), 1599-1606. AlZu'bi, S., Mughaid, A., Quiam, F., &amp; Hendawi, S. (2024). Exploring the capabilities and limitations of chatgpt and alternative big language models. Paper presented at the Artificial Intelligence and Applications. Bacha, M. S., Kumar, T., Bibi, B. S., &amp; Yunus, M. M. (2021). Using English as a lingua franca in Pakistan: Influences and implications in English Language Teaching (ELT). Asian ESP Journal, 17(2), 155-175. Baidoo-Anu, D., &amp; Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. Bansal, H., &amp; Khan, R. (2018). A review paper on human computer interaction. International Journal of Advanced Research in Computer Science and Software Engineering, 8(4), 53. Bhattacherjee, A. (2000). Acceptance of e-commerce services: the case of electronic brokerages. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and humans, 30(4), 411-420. Bylund, E., Khafif, Z., &amp; Berghoff, R. (2024). Linguistic and geographic diversity in research on second language acquisition and multilingualism: An analysis of selected journals. Applied Linguistics, 45(2), 308-329. Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., &amp; Sun, L. (2023). A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt. arXiv preprint arXiv:2303.04226. Chai, C. 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GEN, Boston, MA: Pearson Education, Inc, 10. Ghafar, Z. N., Salh, H. F., Abdulrahim, M. A., Farxha, S. S., Arf, S. F., &amp; Rahim, R. I. (2023). The role of artificial intelligence technology on English language learning: A literature review. Canadian Journal of Language and Literature Studies, 3(2), 17-31. Hair, J. F., Anderson, R. E., Tatham, R. L., &amp; Black, W. C. (1998). Multivariate data analysis. Englewood Cliff. New jersey, USA, 5(3), 207-2019. Hair, J. F., Risher, J. J., Sarstedt, M., &amp; Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24. Haleem, A., Javaid, M., &amp; Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil transactions on benchmarks, standards and evaluations, 2(4), 100089. Henseler, J., Ringle, C. M., &amp; Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43, 115-135. Hosseini, M., Gao, C. A., Liebovitz, D. M., Carvalho, A. M., Ahmad, F. S., Luo, Y., . . . Kho, A. (2023). An exploratory survey about using ChatGPT in education, healthcare, and research. Plos one, 18(10), e0292216. Iku-Silan, A., Hwang, G.-J., &amp; Chen, C.-H. (2023). Decision-guided chatbots and cognitive styles in interdisciplinary learning. Computers &amp; Education, 201, 104812. Khan, I. U., Hameed, Z., &amp; Hamayun, M. (2019). Investigating the acceptance of electronic banking in the rural areas of Pakistan: An application of the unified model. Business and Economic Review, 11(3), 57-87. Khan, I. U., Hameed, Z., Yu, Y., Islam, T., Sheikh, Z., &amp; Khan, S. U. (2018). Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory. Telematics and Informatics, 35(4), 964-978. Kim, A. J.-Y., &amp; Ko, E.-J. (2010). The impact of design characteristics on brand attitude and purchase intention-focus on luxury fashion brands. Journal of the Korean Society of Clothing and Textiles, 34(2), 252-265. Le, T. M. D., Do, H. T. N., Tran, K. M., Dang, V. T., &amp; Nguyen, B. K. H. (2024). Integrating Tam and UGT to explore students’ motivation for using ChatGPT for learning in Vietnam. Journal of Research in Innovative Teaching &amp; Learning. Lenneberg, E. H. (1967). Biological foundations of language. In: Wiley. Liu, G., &amp; Ma, C. (2024). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 18(2), 125-138. Liu, H., Chu, H., Huang, Q., &amp; Chen, X. (2016). Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce. Computers in Human Behavior, 58, 306-314. Lund, B. D., &amp; Wang, T. (2023). Chatting about ChatGPT: how may AI and GPT impact academia and libraries? Library hi tech news, 40(3), 26-29. Mahboob, A. (2021). English in Pakistan: Past, present and future. In English in East and South Asia (pp. 75-89): Routledge. Malik, T., Dwivedi, Y., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., . . . Raghavan, V. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International journal of information management, 71, 102642. Nunally, J. C., &amp; Bernstein, I. (1978). Psychometric theory, ed. New York McGraw. Patel, S. B., &amp; Lam, K. (2023). ChatGPT: the future of discharge summaries? The Lancet Digital Health, 5(3), e107-e108. Peng, M. Y.-P., Xu, Y., &amp; Xu, C. (2023). Enhancing students’ English language learning via M-learning: Integrating technology acceptance model and SOR model. Heliyon, 9(2). 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The term “science” refers to “any system of knowledge that is concerned with the physical world and its phenomena and that entails unbiased observations and systematic experimentation”.1 Therefore, laboratory courses are almost universally considered an integral and mandatory part of instruction on science and technology,2 whatever the field or area of specialization. Consequently, undergraduate chemistry courses (and correlated specialties such as pharmaceutical sciences, biochemistry and some branches of engineering) always include practical disciplines, one of which is instrumental analytical chemistry. Despite being essential for these courses and part of the everyday routine of the faculty affiliated with analytical chemistry departments or programs, several aspects are far from being consensus among lecturers, students and the other people involved. Topics related to course syllabus, general approaches on the implementation and teaching of specific analytical techniques and experiments, their integration with other disciplines, and much more, are a matter of constant discussion and debate. One aspect to be considered is the considerable change in the profile of students that has occurred in recent years. The teaching tools and didactic approaches that university professors and instructors aged &gt; 40 years experienced in their own training are generally not suitable for the present-day undergraduate audience. With former generations, the usual sources of information were printed books and similar materials available in libraries, whereas students today have a greater affinity for consulting online sources,3 which are not always reliable and often return a huge number of search results that require careful evaluation to select which information is relevant and/or reliable. Of course, the facility with which online sources of information are manipulated by our present pupils also has some important advantages: in particular, the near-instantaneous speed of information collection and the virtual accessibility to databases from anywhere on the planet. In addition, until the turn of the millennium, university students were more used to long lectures and experimental classes with relatively complex procedures that often took hours of careful manipulation and numerous laboratory operations (many of them repetitive and tedious). Specifically in the case of practical classes, many of today's students are relatively unaccustomed to experiments that require more than moderate manual skills (at least when compared to their colleagues of previous generations), which may also imply difficulty in organizing their time in the laboratory. Perhaps one of the biggest mistakes we make with our current students is that we consider them ill-prepared or less capable than our generation and attribute their difficulties to this simplistic, crude verdict – when perhaps the biggest problem is that, as educators, we are failing to cope with the rapid evolution in the characteristics and profiles of these young people. The type of change we need so that we can offer practical courses on instrumental analytical chemistry that are more appropriate and better suited for our students is not easy because, in addition to the demand that we change the vision of teaching and paradigms that we have considered as absolute since we entered our academic career, we are also confronted with practical reasons that make this type of change difficult. Laboratory classes demand a huge endeavor from technical and instructional staff and teaching assistants; furthermore, they are comparatively expensive, requiring space, fragile glassware, acquisition and maintenance of instruments, proper disposal of consumables and waste, as well as expenses on faculty salaries.4 The revision of curricula and experimental procedures would impose additional pressure on the workload of the personnel involved and also on the reduced budget availability typical of most public and private universities and colleges (whether in Brazil or anywhere else on the planet). Although there is no easy, direct and universal solution to the problems mentioned above, some alternatives can be tested and adopted with relative ease in most higher education courses on instrumental analytical chemistry. The workload of the experiments can be reduced, supplementing them or eventually even replacing some with practices carried out in virtual environments, which had an unexpected but necessary boost during the recent COVID-19 pandemic.5 Several paid or free-to-use tools have been described for this purpose. For instance, Shallice et al.6 describe a downloadable high-performance liquid chromatography simulator that emulates a basic automated liquid chromatography system capable of binary gradient operation. Similar software emulating other instrumental techniques exist, such as UV-Vis’s spectrometry, electroanalytical techniques, etc., as stand-alone applications, full online resources or even as Excel spreadsheets. In addition to simulated experiments using virtual analytical instruments, other resources that can be used as a supplement to practical instrumental analysis classes are online video libraries, which have also proliferated after the recent period of restriction on face-to-face activities. A well-known example is the collection of the Royal Chemical Society,7 which offers videos demonstrating basic principles and practical aspects of various instrumental techniques (from gas and liquid chromatography to nuclear magnetic resonance spectroscopy). In addition to possible inadequacies due to changes in the profile of typical students currently entering higher education courses in chemistry and related sciences, the evolution of analytical instrumentation, its scope of application and the practical demands imposed on analytical methods that future professionals will apply also pressure us to make changes in the programs of experimental disciplines of instrumental analytical chemistry and in the way we teach the associated techniques. Until the turn of the millennium, the typical program of experimental disciplines of instrumental analytical chemistry in most of the curricula in Brazil and many other countries comprised sequences of isolated experiments using analytical techniques such as gas or liquid chromatography, UV-Vis absorption spectrometry, atomic emission/emission spectrophotometry, etc., with samples and procedures that required relatively simple and quick preparation (usually only sample dissolution, decomposition or extraction). However, due to the natural evolution of analytical instrumentation, the equipment that future professionals will typically find in academic and industrial research laboratories after their impending graduation is very different from that previously employed in the teaching laboratories where their instructors learned analytical chemistry (typically, much simpler equipment that required careful attention and reasonable practical skills from users and operators). The contemporary analytical instruments are much less transparent to the user in their operation; however, as a rule, they incorporate extensive automation and/or mechanization resources, complete control of operation by software and greater operational robustness. From a didactic point of view, modern equipment certainly does not provide students with the same understanding and insight of the basic operational principles of the associated techniques as the instruments of previous generations. However, considering the typical profile of today's students, it possibly would not be advantageous to use those simpler analytical platforms exhaustively merely for didactic purposes. For example, until the turn of the millennium, one of the main demands for students in gas chromatography didactic experiments was to improve and master the manual injection of samples using micro syringes. Today, this didactic approach seems to be preposterous, considering that chromatographs without automatic sample injection are becoming increasingly rare in industrial and even in academic environments. The result is that students are sometimes subjected to tedious laboratory sessions and often completely lose their focus on what would be fundamental in that practical class. In addition, the present demand is increasingly for professionals to be trained to interpret data and propose solutions based on the information gained and not to act as mere operators of laboratory equipment. Thus, it seems to us that we should increasingly design experiments for undergraduate students that incorporate all stages of the analytical process, with particular attention to sampling and sample preparation (taking advantage of features of modern instruments that allow processing more samples in less time and whose operation is less dependent of user ability and manual dexterity) as well as the interpretation and understanding of the analytical data produced. Regarding the above-mentioned focus on the interpretation and understanding of analytical data, it is interesting to note that in 2004, when the Analytical Chemistry Division of the Federation of European Chemical Societies (FECS) established the curricular guidelines to be observed in the analytical chemistry disciplines taught in universities of the European Community (the so-called "Eurocurriculum II"),8 four basic pillars of education in analytical chemistry were defined: Spectroscopy; Chromatography; Chemical Sensors; and Chemometrics and Computer-Based Analytical Chemistry. Thus, it was recognized that in modern analytical chemistry the processing and interpretation of data, as well as its transformation into useful information about the chemical systems studied, is on a par with the three traditional subdivisions of analytical chemistry (spectroscopic and spectrometric techniques, chromatographic techniques and electroanalytical techniques). Although it is important to emphasize that these considerations apply to courses in the European Community, they can be contemplated in the training of chemists anywhere else on the world. Also, they reinforce the indication that the education of analytical chemists should place an increasing emphasis on aspects related to information generation/manipulation and interpretation and not merely on the direct operational aspects of analytical methods and protocols already established. The discussion so far does not pretend to cover all the relevant points whose evaluation would perhaps be necessary for a comprehensive and exhaustive debate of the current status of college/University courses on instrumental analytical chemistry, as well as the possible alternatives and paths to follow. In addition, this text of course echoes the author’s personal opinions and idiosyncrasies, without any pretense at being an absolute expression of the truth (if indeed one exists on this matter). In fact, any discussion of these topics is, by their nature, highly controversial and heavily influenced by the background and area of expertise of those involved. However, we have the firm conviction that the community needs to continuously discuss the education and professional development in analytical chemistry, with emphasis on areas where changes can occur very quickly, always keeping an open mind and a willingness to review supposedly untouchable concepts (and, of course, remembering that its focus should always be on the students).

We’ll have trouble now!The Archaeological Society of Jutland was founded on Sunday, 11 March 1951. As with most projects with which P.V Glob was involved, this did not pass off without drama. Museum people and amateur archaeologists in large numbers appeared at the Museum of Natural History in Aarhus, which had placed rooms at our disposal. The notable dentist Holger Friis, the uncrowned king of Hjørring, was present, as was Dr Balslev from Aidt, Mr and Mrs Overgaard from Holstebro Museum, and the temperamental leader of Aalborg Historical Museum, Peter Riismøller, with a number of his disciples. The staff of the newly-founded Prehistoric Museum functioned as the hosts, except that one of them was missing: the instigator of the whole enterprise, Mr Glob. As the time for the meeting approached, a cold sweat broke out on the foreheads of the people present. Finally, just one minute before the meeting was to start, he arrived and mounted the platform. Everything then went as expected. An executive committee was elected after some discussion, laws were passed, and then suddenly Glob vanished again, only to materialise later in the museum, where he confided to us that his family, which included four children, had been enlarged by a daughter.That’s how the society was founded, and there is not much to add about this. However, a few words concerning the background of the society and its place in a larger context may be appropriate. A small piece of museum history is about to be unfolded.The story begins at the National Museum in the years immediately after World War II, at a time when the German occupation and its incidents were still terribly fresh in everyone’s memory. Therkel Mathiassen was managing what was then called the First Department, which covered the prehistoric periods.Although not sparkling with humour, he was a reliable and benevolent person. Number two in the order of precedence was Hans Christian Broholm, a more colourful personality – awesome as he walked down the corridors, with his massive proportions and a voice that sounded like thunder when nothing seemed to be going his way, as quite often seemed to be the case. Glob, a relatively new museum keeper, was also quite loud at times – his hot-blooded artist’s nature manifested itself in peculiar ways, but his straight forward appearance made him popular with both the older and the younger generations. His somewhat younger colleague C.J. Becker was a scholar to his fingertips, and he sometimes acted as a welcome counterbalance to Glob. At the bottom of the hierarchy was the student group, to which I belonged. The older students handled various tasks, including periodic excavations. This was paid work, and although the salary was by no means princely, it did keep us alive. Student grants were non-existent at the time. Four of us made up a team: Olfert Voss, Mogens Ørsnes, Georg Kunwald and myself. Like young people in general, we were highly discontented with the way our profession was being run by its ”ruling” members, and we were full of ideas for improvement, some of which have later been – or are being – introduced.At the top of our wish list was a central register, of which Voss was the strongest advocate. During the well over one hundred years that archaeology had existed as a professional discipline, the number of artefacts had grown to enormous amounts. The picture was even worse if the collections of the provincial museums were taken into consideration. We imagined how it all could be registered in a card index and categorised according to groups to facilitate access to references in any particular situation. Electronic data processing was still unheard of in those days, but since the introduction of computers, such a comprehensive record has become more feasible.We were also sceptical of the excavation techniques used at the time – they were basically adequate, but they badly needed tightening up. As I mentioned before, we were often working in the field, and not just doing minor jobs but also more important tasks, so we had every opportunity to try out our ideas. Kunwald was the driving force in this respect, working with details, using sections – then a novelty – and proceeding as he did with a thoroughness that even his fellow students found a bit exaggerated at times, although we agreed with his principles. Therkel Mathiassen moaned that we youngsters were too expensive, but he put up with our excesses and so must have found us somewhat valuable. Very valuable indeed to everyon e was Ejnar Dyggve’s excavation of the Jelling mounds in the early 1940s. From a Danish point of view, it was way ahead of its time.Therkel Mathiassen justly complained about the economic situation of the National Museum. Following the German occupation, the country was impoverished and very little money was available for archaeological research: the total sum available for the year 1949 was 20,000 DKK, which corresponded to the annual income of a wealthy man, and was of course absolutely inadequate. Of course our small debating society wanted this sum to be increased, and for once we didn’t leave it at the theoretical level.Voss was lucky enough to know a member of the Folketing (parliament), and a party leader at that. He was brought into the picture, and between us we came up with a plan. An article was written – ”Preserve your heritage” (a quotation from Johannes V. Jensen’s Denmark Song) – which was sent to the newspaper Information. It was published, and with a little help on our part the rest of the media, including radio, picked up the story.We informed our superiors only at the last minute, when everything was arranged. They were taken by surprise but played their parts well, as expected, and everything went according to plan. The result was a considerable increase in excavation funds the following year.It should be added that our reform plans included the conduct of exhibitions. We found the traditional way of presenting the artefacts lined up in rows and series dull and outdated. However, we were not able to experiment within this field.Our visions expressed the natural collision with the established ways that comes with every new generation – almost as a law of nature, but most strongly when the time is ripe. And this was just after the war, when communication with foreign colleagues, having been discontinued for some years, was slowly picking up again. The Archaeological Society of Jutland was also a part of all this, so let us turn to what Hans Christian Andersen somewhat provocatively calls the ”main country”.Until 1949, only the University of Copenhagen provided a degree in prehistoric archaeology. However, in this year, the University of Aarhus founded a chair of archaeology, mainly at the instigation of the Lord Mayor, Svend Unmack Larsen, who was very in terested in archaeology. Glob applied for the position and obtained it, which encompassed responsibility for the old Aarhus Museum or, as it was to be renamed, the Prehistoric Museum (now Moesgaard Museum).These were landmark events to Glob – and to me, as it turned out. We had been working together for a number of years on the excavation of Galgebakken (”Callows Hill”) near Slots Bjergby, Glob as the excavation leader, and I as his assistant. He now offered me the job of museum curator at his new institution. This was somewhat surprising as I had not yet finished my education. The idea was that I was to finish my studies in remote Jutland – a plan that had to be given up rather quickly, though, for reasons which I will describe in the following. At the same time, Gunner Lange-Kornbak – also hand-picked from the National Museum – took up his office as a conservation officer.The three of us made up the permanent museum staff, quickly supplemented by Geoffrey Bibby, who turned out to be an invaluable colleague. He was English and had been stationed in the Faeroe Islands during the war, where he learned to speak Danish. After 1945 he worked for some years for an oil company in the Gulf of Persia, but after marrying Vibeke, he settled in her home town of Aarhus. As his academic background had involved prehistoric cultures he wanted to collaborate with the museum, which Glob readily permitted.This small initial flock governed by Glob was not permitted to indulge inidleness. Glob was a dynamic character, full of good and not so good ideas, but also possessing a good grasp of what was actually practicable. The boring but necessary daily work on the home front was not very interesting to him, so he willingly handed it over to others. He hardly noticed the lack of administrative machinery, a prerequisite for any scholarly museum. It was not easy to follow him on his flights of fancy and still build up the necessary support base. However, the fact that he in no way spared himself had an appeasing effect.Provincial museums at that time were of a mixed nature. A few had trained management, and the rest were run by interested locals. This was often excellently done, as in Esbjerg, where the master joiner Niels Thomsen and a staff of volunteers carried out excavations that were as good as professional investigations, and published them in well-written articles. Regrettably, there were also examples of the opposite. A museum curator in Jutland informed me that his predecessor had been an eager excavator but very rarely left any written documentation of his actions. The excavated items were left without labels in the museum store, often wrapped in newspapers. However, these gave a clue as to the time of unearthing, and with a bit of luck a look in the newspaper archive would then reveal where the excavation had taken place. Although somewhat exceptional, this is not the only such case.The Museum of Aarhus definitely belonged among the better ones in this respect. Founded in 1861, it was at first located at the then town hall, together with the local art collection. The rooms here soon became too cramped, and both collections were moved to a new building in the ”Mølleparken” park. There were skilful people here working as managers and assistants, such as Vilhelm Boye, who had received his archaeological training at the National Museum, and later the partners A. Reeh, a barrister, and G.V. Smith, a captain, who shared the honour of a number of skilfully performed excavations. Glob’s predecessor as curator was the librarian Ejler Haugsted, also a competent man of fine achievements. We did not, thus, take over a museum on its last legs. On the other hand, it did not meet the requirements of a modern scholarly museum. We were given the task of turning it into such a museum, as implied by the name change.The goal was to create a museum similar to the National Museum, but without the faults and shortcomings that that museum had developed over a period of time. In this respect our nightly conversations during our years in Copenhagen turned out to be useful, as our talk had focused on these imperfections and how to eradicate them.We now had the opportunity to put our theories into practice. We may not have succeeded in doing so, but two areas were essentially improved:The numerous independent numbering systems, which were familiar to us from the National Museum, were permeating archaeological excavation s not only in the field but also during later work at the museum. As far as possible this was boiled down to a single system, and a new type of report was born. (In this context, a ”report” is the paper following a field investigation, comprising drawings, photos etc. and describing the progress of the work and the observations made.) The instructions then followed by the National Museum staff regarding the conduct of excavations and report writing went back to a 19th-century protocol by the employee G.V. Blom. Although clear and rational – and a vast improvement at the time – this had become outdated. For instance, the excavation of a burial mound now involved not only the middle of the mound, containing the central grave and its surrounding artefacts, but the complete structure. A large number of details that no one had previously paid attention to thus had to be included in the report. It had become a comprehensive and time-consuming work to sum up the desultory notebook records in a clear and understandable description.The instructions resulting from the new approach determined a special records system that made it possible to transcribe the notebook almost directly into a report following the excavation. The transcription thus contained all the relevant information concerning the in vestigation, and included both relics and soil layers, the excavation method and practical matters, although in a random order. The report proper could then bereduced to a short account containing references to the numbers in the transcribed notebook, which gave more detailed information.As can be imagined, the work of reform was not a continuous process. On the contrary, it had to be done in our spare hours, which were few and far between with an employer like Glob. The assignments crowded in, and the large Jutland map that we had purchased was as studded with pins as a hedge hog’s spines. Each pin represented an inuninent survey, and many of these grew into small or large excavations. Glob himself had his lecture duties to perform, and although he by no means exaggerated his concern for the students, he rarely made it further than to the surveys. Bibby and I had to deal with the hard fieldwork. And the society, once it was established, did not make our lives any easier. Kuml demanded articles written at lightning speed. A perusal of my then diary has given me a vivid recollection of this hectic period, in which I had to make use of the evening and night hours, when the museum was quiet and I had a chance to collect my thoughts. Sometimes our faithful supporter, the Lord Mayor, popped in after an evening meeting. He was extremely interested in our problems, which were then solved according to our abilities over a cup of instant coffee.A large archaeological association already existed in Denmark. How ever, Glob found it necessary to establish another one which would be less oppressed by tradition. Det kongelige nordiske Oldsskriftselskab had been funded in 1825 and was still influenced by different peculiarities from back then. Membership was not open to everyone, as applications were subject to recommendation from two existing members and approval by a vote at one of the monthly lecture meetings. Most candidates were of course accepted, but unpopular persons were sometimes rejected. In addition, only men were admitted – women were banned – but after the war a proposal was brought forward to change this absurdity. It was rejected at first, so there was a considerable excitement at the January meeting in 1951, when the proposal was once again placed on the agenda. The poor lecturer (myself) did his best, although he was aware of the fact that just this once it was the present and not the past which was the focus of attention. The result of the voting was not very courteous as there were still many opponents, but the ladies were allowed in, even if they didn’t get the warmest welcome.In Glob’s society there were no such restrictions – everyone was welcome regardless of sex or age. If there was a model for the society, it was the younger and more progressive Norwegian Archaeological Society rather than the Danish one. The main purpose of both societies was to produce an annual publication, and from the start Glob’s Kuml had a closer resemblance to the Norwegian Viking than to the Danish Aarbøger for nordisk Oldkyndighed og Historie. The name of the publication caused careful consideration. For a long time I kept a slip of paper with different proposals, one of which was Kuml, which won after having been approved by the linguist Peter Skautrup.The name alone, however, was not enough, so now the task became to find so mething to fill Kuml with. To this end the finds came in handy, and as for those, Glob must have allied him self with the higher powers, since fortune smiled at him to a considerable extent. Just after entering upon his duties in Aarhus, an archaeological sensation landed at his feet. This happened in May 1950 when I was still living in the capital. A few of us had planned a trip to Aarhus, partly to look at the relics of th e past, and partly to visit our friend, the professor. He greeted us warmly and told us the exciting news that ten iron swords had been found during drainage work in the valley of lllerup Aadal north of the nearby town of Skanderborg. We took the news calmly as Glob rarely understated his affairs, but our scepticism was misplaced. When we visited the meadow the following day and carefully examined the dug-up soil, another sword appeared, as well as several spear and lance heads, and other iron artefacts. What the drainage trench diggers had found was nothing less than a place of sacrifice for war booty, like the four large finds from the 1800s. When I took up my post in Aarhus in September of that year I was granted responsibility for the lllerup excavation, which I worked on during the autumn and the following six summers. Some of my best memories are associated with this job – an interesting and happy time, with cheerful comradeship with a mixed bunch of helpers, who were mainly archaeology students. When we finished in 1956, it was not because the site had been fully investigated, but because the new owner of the bog plot had an aversion to archaeologists and their activities. Nineteen years later, in 1975, the work was resumed, this time under the leadership of Jørgen Ilkjær, and a large amount of weaponry was uncovered. The report from the find is presently being published.At short intervals, the year 1952 brought two finds of great importance: in Februar y the huge vessel from Braa near Horsens, and in April the Grauballe Man. The large Celtic bronze bowl with the bulls’ heads was found disassembled, buried in a hill and covered by a couple of large stones. Thanks to the finder, the farmer Søren Paaske, work was stopped early enough to leave areas untouched for the subsequent examination.The saga of the Grauballe Man, or the part of it that we know, began as a rumour on the 26th of April: a skeleton had been found in a bog near Silkeborg. On the following day, which happened to be a Sunday, Glob went off to have a look at the find. I had other business, but I arrived at the museum in the evening with an acquaintance. In my diary I wrote: ”When we came in we had a slight shock. On the floor was a peat block with a corpse – a proper, well-preserved bog body. Glob brought it. ”We’ll be in trouble now.” And so we were, and Glob was in high spirits. The find created a sensation, which was also thanks to the quick presentation that we mounted. I had purchased a tape recorder, which cost me a packet – not a small handy one like the ones you get nowadays, but a large monstrosity with a steel tape (it was, after all, early days for this device) – and assisted by several experts, we taped a number of short lectures for the benefit of the visitors. People flocked in; the queue meandered from the exhibition room, through the museum halls, and a long way down the street. It took a long wait to get there, but the visitors seemed to enjoy the experience. The bog man lay in his hastily – procured exhibition case, which people circled around while the talking machine repeatedly expressed its words of wisdom – unfortunately with quite a few interruptions as the tape broke and had to be assembled by hand. Luckily, the tape recorders now often used for exhibitions are more dependable than mine.When the waves had died down and the exhibition ended, the experts examined the bog man. He was x-rayed at several points, cut open, given a tooth inspection, even had his fingerprints taken. During the autopsy there was a small mishap, which we kept to ourselves. However, after almost fifty years I must be able to reveal it: Among the organs removed for investigation was the liver, which was supposedly suitable for a C-14 dating – which at the time was a new dating method, introduced to Denmark after the war. The liver was sent to the laboratory in Copenhagen, and from here we received a telephone call a few days later. What had been sent in for examination was not the liver, but the stomach. The unfortunate (and in all other respects highly competent) Aarhus doctor who had performed the dissection was cal1ed in again. During another visit to the bogman’s inner parts he brought out what he believed to be the real liver. None of us were capable of deciding th is question. It was sent to Copenhagen at great speed, and a while later the dating arrived: Roman Iron Age. This result was later revised as the dating method was improved. The Grauballe Man is now thought to have lived before the birth of Christ.The preservation of the Grauballe Man was to be conservation officer Kornbak’s masterpiece. There were no earlier cases available for reference, so he invented a new method, which was very successful. In the first volumes of Kuml, society members read about the exiting history of the bog body and of the glimpses of prehistoric sacrificial customs that this find gave. They also read about the Bahrain expeditions, which Glob initiated and which became the apple of his eye. Bibby played a central role in this, as it was he who – at an evening gathering at Glob’s and Harriet’s home in Risskov – described his stay on the Persian Gulf island and the numerous burial mounds there. Glob made a quick decision (one of his special abilities was to see possibilities that noone else did, and to carry them out successfully to everyone’s surprise) and in December 1952 he and Bibby left for the Gulf, unaware of the fact that they were thereby beginning a series of expeditions which would continue for decades. Again it was Glob’s special genius that was the decisive factor. He very quickly got on friendly terms with the rulers of the small sheikhdoms and interested them in their past. As everyone knows, oil is flowing plentifully in those parts. The rulers were thus financially powerful and some of this wealth was quickly diverted to the expeditions, which probably would not have survived for so long without this assistance. To those of us who took part in them from time to time, the Gulf expeditions were an unforgettable experience, not just because of the interesting work, but even more because of the contact with the local population, which gave us an insight into local manners and customs that helped to explain parts of our own country’s past which might otherwise be difficult to understand. For Glob and the rest of us did not just get close to the elite: in spite of language problems, our Arab workers became our good friends. Things livened up when we occasionally turned up in their palm huts.Still, co-operating with Glob was not always an easy task – the sparks sometimes flew. His talent of initiating things is of course undisputed, as are the lasting results. He was, however, most attractive when he was in luck. Attention normally focused on this magnificent person whose anecdotes were not taken too seriously, but if something went wrong or failed to work out, he could be grossly unreasonable and a little too willing to abdicate responsibility, even when it was in fact his. This might lead to violent arguments, but peace was always restored. In 1954, another museum curator was attached to the museum: Poul Kjærum, who was immediately given the important task of investigating the dolmen settlement near Tustrup on Northern Djursland. This gave important results, such as the discovery of a cult house, which was a new and hitherto unknown Stone Age feature.A task which had long been on our mind s was finally carried out in 1955: constructing a new display of the museum collections. The old exhibitio n type consisted of numerous artefacts lined up in cases, accompaied ony by a brief note of the place where it was found and the type – which was the standard then. This type of exhibition did not give much idea of life in prehistoric times.We wanted to allow the finds to speak for themselves via the way that they were arranged, and with the aid of models, photos and drawings. We couldn’t do without texts, but these could be short, as people would understand more by just looking at the exhibits. Glob was in the Gulf at the time, so Kjærum and I performed the task with little money but with competent practical help from conservator Kornbak. We shared the work, but in fairness I must add that my part, which included the new lllerup find, was more suitable for an untraditional display. In order to illustrate the confusion of the sacrificial site, the numerous bent swords and other weapons were scattered a.long the back wall of the exhibition hall, above a bog land scape painted by Emil Gregersen. A peat column with inlaid slides illustrated the gradual change from prehistoric lake to bog, while a free-standing exhibition case held a horse’s skeleton with a broken skull, accompanied by sacrificial offerings. A model of the Nydam boat with all its oars sticking out hung from the ceiling, as did the fine copy of the Gundestrup vessel, as the Braa vessel had not yet been preserved. The rich pictorial decoration of the vessel’s inner plates was exhibited in its own case underneath. This was an exhibition form that differed considerably from all other Danish exhibitions of the time, and it quickly set a fashion. We awaited Glob’s homecoming with anticipation – if it wasn’t his exhibition it was still made in his spirit. We hoped that he would be surprised – and he was.The museum was thus taking shape. Its few employees included Jytte Ræbild, who held a key position as a secretary, and a growing number of archaeology students who took part in the work in various ways during these first years. Later, the number of employees grew to include the aforementioned excavation pioneer Georg Kunwald, and Hellmuth Andersen and Hans Jørgen Madsen, whose research into the past of Aarhus, and later into Danevirke is known to many, and also the ethnographer Klaus Ferdinand. And now Moesgaard appeared on the horizon. It was of course Glob’s idea to move everything to a manor near Aarhus – he had been fantasising about this from his first Aarhus days, and no one had raised any objections. Now there was a chance of fulfilling the dream, although the actual realisation was still a difficult task.During all this, the Jutland Archaeological Society thrived and attracted more members than expected. Local branches were founded in several towns, summer trips were arranged and a ”Worsaae Medal” was occasionally donated to persons who had deserved it from an archaeological perspective. Kuml came out regularly with contributions from museum people and the like-minded. The publication had a form that appealed to an inner circle of people interested in archaeology. This was the intention, and this is how it should be. But in my opinion this was not quite enough. We also needed a publication that would cater to a wider public and that followed the same basic ideas as the new exhibition.I imagined a booklet, which – without over-popularsing – would address not only the professional and amateur archaeologist but also anyone else interested in the past. The result was Skalk, which (being a branch of the society) published its fir t issue in the spring of 1957. It was a somewhat daring venture, as the financial base was weak and I had no knowledge of how to run a magazine. However, both finances and experience grew with the number of subscribers – and faster than expected, too. Skalk must have met an unsatisfied need, and this we exploited to the best of our ability with various cheap advertisements. The original idea was to deal only with prehistoric and medieval archaeology, but the historians also wanted to contribute, and not just the digging kind. They were given permission, and so the topic of the magazine ended up being Denmark’s past from the time of its first inhabitant s until the times remembered by the oldest of us – with the odd sideways leap to other subjects. It would be impossible to claim that Skalk was at the top of Glob’s wish list, but he liked it and supported the idea in every way. The keeper of national antiquities, Johannes Brøndsted, did the same, and no doubt his unreserved approval of the magazine contributed to its quick growth. Not all authors found it easy to give up technical language and express themselves in everyday Danish, but the new style was quickly accepted. Ofcourse the obligations of the magazine work were also sometimes annoying. One example from the diary: ”S. had promised to write an article, but it was overdue. We agreed to a final deadline and when that was overdue I phoned again and was told that the author had gone to Switzerland. My hair turned grey overnight.” These things happened, but in this particular case there was a happy ending. Another academic promised me three pages about an excavation, but delivered ten. As it happened, I only shortened his production by a third.The 1960s brought great changes. After careful consideration, Glob left us to become the keeper of national antiquities. One important reason for his hesitation was of course Moesgaard, which he missed out on – the transfer was almost settled. This was a great loss to the Aarhus museum and perhaps to Glob, too, as life granted him much greater opportunities for development.” I am not the type to regret things,” he later stated, and hopefully this was true. And I had to choose between the museum and Skalk – the work with the magazine had become too timeconsuming for the two jobs to be combined. Skalk won, and I can truthfully say that I have never looked back. The magazine grew quickly, and happy years followed. My resignation from the museum also meant that Skalk was disengaged from the Jutland Archaeological Society, but a close connection remained with both the museum and the society.What has been described here all happened when the museum world was at the parting of the ways. It was a time of innovation, and it is my opinion that we at the Prehistoric Museum contributed to that change in various ways.The new Museum Act of 1958 gave impetus to the study of the past. The number of archaeology students in creased tremendously, and new techniques brought new possibilities that the discussion club of the 1940s had not even dreamt of, but which have helped to make some of the visions from back then come true. Public in terest in archaeology and history is still avid, although to my regret, the ahistorical 1960s and 1970s did put a damper on it.Glob is greatly missed; not many of his kind are born nowadays. He had, so to say, great virtues and great fault s, but could we have done without either? It is due to him that we have the Jutland Archaeological Society, which has no w existed for half a century. Congr tulat ion s to the Society, from your offspring Skalk.Harald AndersenSkalk MagazineTranslated by Annette Lerche Trolle

Computer and multimedia learning is still an active teaching method. Computer-assisted and computer-based training allows an education based on the intellectual profile of the student and beyond. It also puts the student in situations of interaction and rapid communication, made in a favorable environment that allows massive dissemination of the created content and time flexibility by combining synchronous and asynchronous means of communication. In the case of computer-assisted instruction, the interactivity is practically generalized, providing the learner with permanent feedback, as visible and immediate effects occur on the computer screen. Today, computer-assisted instruction involves efficient research of the student's work, supervised and guided by the teacher (even in the current conditions dictated by the pandemic), which helps him in performing technical operations, in identifying the links between information and documentation, leading him to a new form of knowledge (digital knowledge). Achieving the objectives of the educational process requires as necessary, in different stages of learning, the intuition of processes and phenomena of reality, either directly or through substitutes. At the same time, the formation of skills and abilities requires the presence of material supports for practicing actions. Through this paper, we aim to show that there is thus a diversity in education such as "pedagogical tools" called associated teaching aids in the field of computer-assisted training. They contribute to the efficient development of the didactic activity, being equally material resources of the educational process, selected from reality, modified, or made to reach the pedagogical objectives. The progress of technology has driven the diversification and improvement of these resources, so that, in the Information and Knowledge Society, it can be shown that computer-assisted training has become a variable of the modern educational process, which must take into account, more than ever, the profile of the individual and society.

International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 DOI : 10.5121/ijbb.2012.2401 1 PERSPECTIVES ON COMPUTER ASSISTED SURGERY (CAS) IN MINIMALLY INVASIVE SURGERY AND THE ROLE OF THE CAS SYSTEM NURSE Jo&atilde;o Fradinho Oliveira1 Hugo Capote2 Jos&eacute; Blas Pagador3 Jos&eacute; Luis Moyano Cuevas3 Francisco Miguel S&aacute;nchez Margallo4 1 C3i/Instituto Polit&eacute;cnico de Portalegre, Portalegre, Portugal jfoliveira@estgp.pt 2 Hospital Dr. Jos&eacute; Maria Grande in Portalegre, Portugal hugocapote@gmail.com 3 Bioengineering and Health Technology Unit, Jesus Uson Minimally Invasive Surgery Center, Caceres, Spain {jbpagador, jmoyano}@ccmijesususon.com 4 Jesus Uson Minimally Invasive Surgery Center, Caceres, Spain msanchez@ccmijesususon.com ABSTRACT Minimally invasive surgery has become a widely used surgical technique that improves patients&rsquo; safety and optimizes health resources. Specifically, laparoscopic surgery uses small incisions through the abdomen to operate, for example a liver, with minimal postoperative complications and faster recoveries. However, the cognitive load and surgical skills required by surgeons increase when compared to open surgery. For these reasons, specific training models and new technologies are needed to assist surgeons. One of this kind of systems are Computer Assisted Surgery systems that enable the display of computer generated imagery of pre- and intra-operative data to assist surgeons during its surgical procedures, but in many hospitals either they are not used at a basic level due to socio-economic challenges or components still face considerable technical challenges that must be solved. In this paper we list some of the difficulties that CAS components face during a laparoscopic surgery and highlight the benefits that a new job profile, the computer assisted surgery system nurse could bring in several modelling and tracking scenarios. KEYWORDS Laparoscopic surgery, 3D reconstruction, navigation, tracking, computer assisted surgery system nurse 1. INTRODUCTION Laparoscopic surgery has become a gold standard technique in many surgical interventions for the last years. Mainly due to its multiple safety advantages for patients and important health cost reductions [1]. However some minimally invasive procedures are complex and need additional technologies that assist and enhance surgeon performance. In this case, Image-Guided Interventions (IGI) or Computer Assisted Surgery (CAS) are very active research fields. Haigron et. al [2] makes an overview to the newest Image Guided Therapies (IGT). In order to best understand the physical and environmental constraints present in laparoscopic surgery, we refer the reader to Figure 1 and 2. Figure 1 shows the set-up of a laparoscopic surgery with a video display and the placement of 4 trocars: endoscope (video camera unit with light) and 3 laparoscopic instruments (forceps, retractor, scissors or dissectors). International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 2 Figure 1. An example laparoscopic surgery set-up that uses 4 inserted trocars: 1) camera providing video images from inside the patient on the screen 2) scissors 3) retractor instrument to achieve adequate exposure of the surgical field 4) iron to stop bleeds Figure 2. Typical video image of a laparoscopic surgery In addition sometimes aspiration/flushing or haemostasis instruments are used during surgery. Currently, there are different surgical procedures that modify the number and location of trocars depending on their needs. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 3 Figure 2 shows an example of the surgical scene, where one can see that the field of view of the endoscopic camera is very limited, and that most of the time only partial views of the organs will be possible. Among other limitations the reduced workspace environment, cognitive load, limited tactile perception and difficulties with hand-eye coordination are the most important problems for surgeons. The endoscopic camera can fog up or be smudged with blood during surgical procedure and has to be removed, cleaned and re-inserted. Furthermore, the focus of the camera may also require manual adjustment. In the other hand, the task of reaching the target location to be operated can be regarded as exploratory, as organs are shifting with the breathing cycle of the patient, organs need to be temporarily moved aside to access other structures and the expected anatomy can have considerable differences in shape, position, texture and colour to the one observed. Once the target area of surgery is reached, a trained surgeon can remove, clean, re-insert the camera and find the previous target with a great speed by memorizing the tactile information and actual organ placement. Finally, in a typical operation usually a second surgeon is responsible for handling the camera, retracting the organs and assists the surgery, whilst an assisting nurse has the role of instrumenting the surgery and provides anything that is needed during the operation. The remainder of the paper is organized as follows: in section II we broadly categorize four CAS research areas, describe some of the challenges and limitations that they face during a real operation and list four specific problems that we believe can be addressed with a new job profile, the CAS system nurse which is presented in section III. We present future work in section IV followed by conclusions. 2. BACKGROUND &amp; RELATED WORK The most basic computer assisted surgery system shows pre-operative data (CT or US/ Figure 3) during the surgical procedure together with live video from the endoscopic camera. These images can include resection maps, highlights of vein structures and are useful to lessen the cognitive load of the surgeon. More sophisticated CAS systems enable the display/overlay of 3D reconstructed computer models of organs; to track the position of instruments and render them in the reference frame of pre or intra-operative images; and to program robot arms to perform precision critical tasks. Many of these complex systems use techniques from medical image processing, computer graphics, robotics, virtual and augmented reality that are adapted with varying degrees of success to the type operation at hand, set-up and image modality being used. In this section we present some of the main problems that the classical techniques in these fields face in the laparoscopic surgery context, and list four that we believe can be addressed by the CAS system nurse. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 4 Figure 3. Ultrasound image. 2.1. 3D model representation Computed tomography (CT) and Magnetic Resonance imaging (MRI) scanners create collections of 2D images (pixels) that can be viewed in various planes (eg. axial, coronal, sagittal) or 3D data (voxels) that can be visualized using volume rendering techniques. Whilst these representations are useful for visual inspection and calculations, iso-surface extraction methods that create polygonal surface meshes (polygons) with algorithms such as the marching cubes allow one to create a variety of other applications, for example: 3D printing of implants using standard 3D editing tools for mirroring and cutting the model, the creation of soft tissue models: (tetrahedral) using surface offsets for finite element simulation of surgical procedures with haptic devices, or used as input for Spring-Damper-Mass systems where point masses (nodes) are inter-connected by elastic springs corresponding to the edges of the initial polygonal mesh. Finally polygonal surfaces can be used for pre-operative resection map renderings. Whilst the above representations are useful in the context of some simulations, in the context intra-operative imaging, they cannot robustly capture the i) drastic morphological changes made to soft tissues during the operation. For example, significant layers of fat or soft tissue are often cut and removed in order to access the main blood supply of the spleen during a spleen removal procedure, or when removing a tumour from a kidney the kidney can be reduced to 30% of its original volume making the original 3D model somewhat useless if ii) superimposed over corresponding parts in the live video. Furthermore real organs can bend beyond the integrity of soft models. Implicit surfaces such as Metaballs are a somewhat more organic representation, but unfortunately there is no direct conversion from polygon model to metaballs [3], and they are not very accurate [4]. 2.2. Tracking and Registration Non-rigid registration relies on creating correspondences between the features in the video stream and the 3D models. Unfortunately as can be seen in Figure 2 many times only iii) partial views of organs are seen, making non-registration inherently a difficult task to be done with few International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 5 visible markers. According to Peters and Cleary [5], one of the most important unsolved problems of IGI is non-rigid registration. From our point of view, there are two different problems to solve in this field of research. On one side, recent research of surgical instrument tracking is focused on solving their position and velocity using video analysis techniques [6]. On the other hand, several problems with organ shift and tissue deformation are the most important challenges for the registration techniques [7]. As Baumhauer et al. [7] suggest, maybe current limitations in navigation systems could be solved using a closer collaboration between different surgical actors. In conclusion, tracking techniques can be divided in two groups according to their use natural or artificial landmarks to track the objects of interest. 2.3. Mental map &amp; Navigation Surgical navigation belongs to the broad field of computer assisted surgery. The intraoperative surgical navigation systems allow the surgeon to identify the anatomical structures involved and to know the spatial relationship between the target and risk structures of the surgery. However, intraoperative navigation in soft tissue presents major complications associated with the deformation of the organs during surgery. This problem leads to the situation that anatomical structures have changed from the planning done by the surgeon, so the system must adapt the preoperative information to the intraoperative situation. This problem is a very interesting and challenging research field. Different methods have been proposed to solve the problem of the soft tissue deformation. In minimally invasive surgery, the methods are mainly based on the use of intraoperative imaging and tracking systems [8-10]. One solution to the deformation produced by the movement of the organ was described by Zhang et al. [11], who compensate organ motion using an electromagnetic tracking system. Despite all efforts, the simulation of deformations in some interventions such as liver surgery is a complicated task and actually some improvements are required [12]. Lamata et al. [12] propose an intermediate system for assisting minimally invasive liver resection. This approach shows the resection map preoperatively planned during surgery, allowing the surgeon to perform an alignment between the map of resection and the operating field. We think that the accurate intraoperative deformation can be achieved through the intervention of an assistant that will interact with the CAS system manually. However, it is necessary to have a iv) suitable profile to identify anatomical structures in different intraoperative images and operate a computer assisted surgery. Another problem of the intraoperative navigation system is its management during surgery, as the surgeon can&rsquo;t interact directly with the system. Therefore, it is essential that the assistant operates with the system during surgery. It is also necessary that the surgeon&#39;s instructions are clearly interpretable and reproducible by the assistant in the navigation system [7], because otherwise it may hamper the intervention. 2.4. Haptics &amp; Robotics Robotic Minimally Invasive Surgery (RMIS) is a high rising technique in the last years that enhances accuracy and safety of surgical procedures [14]. However, current robotic systems for surgery are not fully integrated with surgical planning and navigation systems. For this reason, pre- and intra-operative imaging guidance are one of the most important field of research needed to integrate the specific models of the patient with robotic systems or smart surgical tools. MRI mechanical manipulators [13] and visual servoing [14] techniques are shown as some of the most promising results, although all of these developments are focused on the visual sense as the main source of information for the surgeon. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 6 On the other hand, touch sense problems in MIS are well known [16] and some studies demonstrate that the lack of touch feedback in MIS can increase intra-operative injury [15]. Therefore, one important trend in RMIS could be considered as force feedback of robotic surgical systems that allows for surgeons to have similar touching sensations like in open surgery [17]. Furthermore, tactile feedback is another feature lacking in MIS that should be solved in future developments [18]. 3. THE CAS SYSTEM NURSE As mentioned previously Computer Assisted Surgery systems at a basic level allow for the display of live video images from the endoscopic camera and the display of preoperative images during the operation hence lessening the cognitive load of the surgeon. In the previous section we listed the following four problems in intra-operative imaging that we believe can be addressed with a new job profile, the computer assisted surgery nurse: i) Drastic morphological changes ii) Superimposed over corresponding parts iii) Partial views of organs iv) Suitable profile In this section we present the CAS system nurse, and how this new job profile can address each of the four problems. Superimposed over corresponding parts Although existing 3D representations can have a supporting role during surgery, the inconsistencies from pre- and intra-operation could block the video information. To solve this, the models could be rendered in a separate viewport. The CAS nurse could then make real-time adjustments to the 3D reconstructed models such as scaling and rotation. Drastic morphological changes The CAS nurse could use sliders to control the transparency level of objects that no longer correspond to the intra-operative data. Ideally lines of a 3D grid could be superimposed over the rendered object (polygonal surface or volumetric render), and the CAS nurse could change the transparency level of each cube. Removed parts by the surgeon would be completely transparent. In the case of multiple enclosed surfaces of for example a tumour enclosed in the liver, the whole liver object could be selected by the CAS nurse and have its transparency increased in order for the surgeon to see the surface rendering of the tumour. Partial views of organs As mentioned earlier, tracking algorithms have significant difficulties to find correspondences with partial views of organs. We suggest that the human can beat these algorithms while they are not fully reliable yet, the CAS nurse can manually align the 3D models so as to have the same pose/orientation of the parts of organs that are indeed visible. The models could also be zoomed so as to focus the rendering in the working area. Suitable profile In order for the CAS nurse to be able to identify from video images organs with partial views, the CAS nurse would need to undergo several hours of training, attending real laparoscopic surgeries. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 7 The CAS nurse could respond to specific voice commands from the surgeon during the operation; such as changing the content of a particular viewport (e.g. Figure 4), access a preoperation file, zoom or un-zoom the 3D rendering, or rotate the 3D model. These voice commands could be formalized, thus ensuring that the training for this job profile could be then used in different countries and hospitals. Figure 4. The CGI nurse overlays preoperative CT data over live intraoperative video images 4. FUTURE WORK We are developing a new CAS system, where two intra-operating video feeds will be captured and displayed (ultrasound and endoscopic camera). The system will allow the CAS nurse to pause any of the feeds, it will have separate configurable viewports for the display of preoperation data, one of the viewports will allow the CAS nurse to rotate, and scale the 3D reconstructed organs to align them with the data from the video feed. Finally the system will enable the slice marking of veins, organs and tumours to create 3D reconstructions. We hope that these new capabilities of CAS nurse will help both the exploratory phase of the surgery (find the organ) and the actual surgery where resection maps and transparency control of removed parts should be possible. 5. CONCLUSIONS We have reviewed some of the main problems of existing CAS systems for adapting preoperation data during the surgery. Four specific aspects were listed, and a new job profile that could address those aspects was presented. It is hoped that this new job profile could help in the operation room whilst existing techniques are further developed. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 8 ACKNOWLEDGEMENTS The authors would like to thank the medical staff from Hospital Dr. Jos&eacute; Maria Grande in Portalegre Portugal for their cooperation and Red de Investigaci&oacute;n Transfronteriza de Extremadura Centro y Alentejo. This project is funded by Programa de Cooperaci&oacute;n Transfronteriza Espa&ntilde;a Portugal (POCTEP) and Fondo Europeo de Desarrollo Regional (FEDER) Reference code: 0401_RITECA_II_4_E. REFERENCES [1] da Luz Moreira, A. &amp; Kiran, R. P. &amp; Kirat, H. T. &amp; Remzi, F. H. &amp; Geisler, D. P. &amp; Church, J. M. &amp; Garofalo, T. &amp; Fazio, V. W., (2010) &ldquo;Laparoscopic versus open colectomy for patients with American Society of Anesthesiology (ASA) classification 3 and 4: the minimally invasive approach is associated with significant quicker recovery and reduced costs&rdquo;, Surgical Endoscopy, Vol. 24, No. 6, pp1280-1286. [2] Haigron, P. &amp; Dillenseger, J. L., (2010) &ldquo;Image-guided therapy: evolution and breakthrough&rdquo;, IEEE Engineering in Medicine and Biology Magazine, Vol. 29, No. 1, pp100-104, doi:10.1109/MEMB.2009.935459. [3] Boothroyd, A. &amp; etc, (2012) &ldquo;Mesh cutting algorithm for an orthopaedic surgery simulator&rdquo;, blah [4] De Novi, G., (2011) &ldquo;Soft Tissue Modeling for Virtual Reality Surgery Simulator with Haptic Feedback&rdquo;, PhD Thesis, Universit&agrave; di Bologna. [5] Peters, T. &amp; Cleary, K., (2008) &rdquo;Image-Guided Interventions&rdquo;, Technology and Applications, Springer, ISBN 978-0-387-73856-7. [6] Doignon, C. &amp; Nageotte, F. &amp; Maurin, B. &amp; Krupa, A., (2008) &ldquo;Pose estimation and Feature Tracking for Robot Assisted Surgery with Medical Imaging&rdquo;, Unifying Perspectives in Computational and Robot Vision Lecture Notes in Electrical Engineering, Springer, Vol. 8, pp79-101. 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Cleary K., (2006), &ldquo;Electromagnetic tracking for abdominal interventions in computer aided surgery&rdquo; Comput Aided Surg, Vol. 11, No. 3, pp127-36. [12] Lamata, P. &amp; Lamata, F. &amp; Sojar, V. &amp; Makowski, P. &amp; Massoptier, L. &amp; Casciaro, S. &amp; Ali, W. &amp; St&uuml;deli, T. &amp; Declerck &amp; Elle, O. J. &amp; Edwin, B. (2010) &ldquo;Use of the Resection Map system as guidance during hepatectomy&rdquo;, Springer Surgical Endoscopy, Vol. 24, No. 9. [13] Tsekos, N. V. &amp; Khanicheh, A., Christoforou, E. &amp; Mavroidis C., (2007) &ldquo;Magnetic resonancecompatible robotic and mechatronics systems for image-guided interventions and rehabilitation: a review study&rdquo;, Annual review of biomedical engineering, Vol. 9, No. 5, pp351-87, doi:10.1146/annurev.bioeng.9.121806.160642. [14] Ed. Bozovic, V., (2008) &ldquo;Medical Robotics&rdquo;, I-Tech Education and Publishing, ISBN 978-3- 902613-18-9. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 9 [15] Xin, H. &amp; Zelek, J. S. &amp; Carnahan, H., (2006) &ldquo;Laparoscopic surgery, perceptual limitations and force: A review&rdquo;, In First Canadian Student Conference on Biomedical Computing, Kingston, Ontario, Canada, 2006. No. 144. [16] Westebring-van der Putten, E. P. &amp; Goossens, R. H. &amp; Jakimowicz, J. J. &amp; Dankelman, J., (2008) &ldquo;Haptics in minimally invasive surgery--a review&rdquo;, Minim Invasive Ther Allied Technol. Vol. 17, No. 1, pp3-16. [17] Okamura, A. M. &amp; Verner, L. N. &amp; Reiley, C. E. &amp; Mahvash, M., (2007) &ldquo;Haptics for RobotAssisted Minimally Invasive Surgery&rdquo;, In 13th International Symposium of Robotics Research (ISRR 2007), Hiroshima, Japan, 2007. [18] Nguan, C. &amp; Girvan, A. &amp; Luke, P. P., (2008) &ldquo;Robotic surgery versus laparoscopy: a comparison between two robotic systems and laparoscopy&rdquo;, J Robotic Surg, 1:263-268, doi:10.1007/s11701-007-0050-x. Authors Jo&atilde;o Fradinho Oliveira holds a PhD in Computer Science (Geometry reduction) from University College London. He finished his post-doc in outof-core visualization techniques at INESC-ID (Computer Systems Engineering Institute) in 2011. He is currently adjunct Professor at Instituto Polit&eacute;cnico de Portalegre, Escola Superior de Tecnologia e Gest&atilde;o, where he teaches 3D programming. His main interests are point cloud processing and 3D visualization systems. He has published 18 papers. Hugo Chichorro e Silva Capote graduated in Medicine, in 2001, in the Medical School of the Coimbra University, Portugal. In 2009, after 6 years of formation in the Hospital of Portalegre he obtained the degree of Assistant in the specialty of General Surgery. Since then he works as a Surgeon in Portalegre, being one of the staff that is responsible for the Coloproctology Unit of the Department of Surgery. He works routinely with laparoscopy, performing several different techniques, after having trained in Strasbourg at IRCAD and C&aacute;ceres at CCMI. He has published papers on different subjects, such as colon and small bowel pathology and some clinical cases. Jose Blas Pagador is the Head Manager of the Bioengineering and Health Technologies Unit within Jes&uacute;s Us&oacute;n Minimally Invasive Surgery Centre. He is a Master Engineer in Computer Science from the University of Extremadura, specialized on Minimally Invasive Surgery Devices and Technologies. One of his main research interests is focused on surgical training and assessment. He has participated in 21 research projects and he has published 16 papers and more than 50 communications. He has organized 2 International Scientific Meetings Jose Luis Moyano Cuevas. Obtained his Informatic Engineer degree in 2007 at the University of Extremadura where he got a research fellowship on mobile technologies. In 2012, he obtained the Master Engineer in Computer Science at University of Extremadura. Since 2008, he works as a researcher at the Bioengineering and Health Technologies Unit at Jes&uacute;s Us&oacute;n Minimally Invasive Surgery Centre. His main research lines are medical image and the computer assisted surgery. He has participated in five research projects and he is co-author of the 7 publications in journals. International Journal on Bioinformatics &amp; Biosciences (IJBB) Vol.2, No.4, December 2012 10 Francisco Miguel S&aacute;nchez Margallo is Scientific Director of the Jes&uacute;s Us&oacute;n Minimally Invasive Surgery Centre and Doctor of Veterinary Science at the University of Extremadura. Instructor in more than 400 training activities in minimally invasive surgery. Professor and organizer of more than 375 national and international courses for practical training of surgeons and health professionals. Author of 86 scientific articles published in magazines with Impact Factor and author and co-author of more than 79 articles of diffusion related to Minimally Invasive Surgery and Surgery. Author of 10 books and co-author of 45 book chapters. Author of 100 scientific posters, over 300 invited lectures and free communications presented at national and international congresses. He has participated in 67 research projects funded by public entities and companies. He is also member of several scientific and organization committees in different symposium and conferences, as well as reviewer of scientific journals.

Families of children with developmental disabilities in rural and underserved areas may lack access to direct service providers. Global pandemics such as COVID-19 have further affected access to service providers for most children, often shifting services online and increasing the role of technology and involvement of parents and caregivers in intervention. Thus, there is a need to examine the characteristics and effects of caregiver implemented technology-based interventions for children with developmental disabilities. The present synthesis evaluates the research on caregiver implemented technology-based interventions for children with autism spectrum disorder and other developmental disabilities aged 21 or younger. A systematic search of four electronic databases resulted in 14 single-case design studies which encompassed 58 participants with a developmental disability, along with 62 caregivers. Studies used a variety of technologies and involved strategies such as computer assisted instruction, self-management, and variations of video modeling. Interventions targeted a variety of outcomes and most incorporated behavioral strategies such as prompting or positive reinforcement. Results indicate positive outcomes without overly time intensive parent training; however, it is important to consider these findings within context of methodological strength, as only four included studies utilized strong experimental methods according to the evaluative framework provided by Reichow et al. (2008) . Implications for practice and recommendations for future research are provided.

Abstract Although a substantial body of research has examined how sustainability is integrated into higher education curricula, relatively few studies have explored how instructors incorporate climate and environmental justice (CEJ) content and pedagogies across disciplines. Emerging scholarship has begun to address how interdisciplinary environmental and sustainability (IES) programs and institutional sustainability requirements include environmental justice (EJ) course content. Yet when CEJ knowledge is not broadly embedded across disciplines by IES faculty or institutional leaders, the resulting curricular gaps often exclude the content, practices, and lived experiences of those most affected by global environmental and climate challenges. This exclusion, especially common in STEM-focused areas, can have significant consequences for underrepresented students. This study investigates these dynamics within a STEM institutional context, examining how faculty and instructors incorporated CEJ content and pedagogy across 11 courses at a four-year, private, technical institution. Using a case-study approach and multiple data sources, the study identifies four clusters within a spectrum of CEJ inclusion, each characterized by distinct experiential pedagogies such as community engagement, transdisciplinary methods, and the use of diverse epistemologies. The findings also reveal that CEJ content was most often integrated into STEM courses through collaboration with the social sciences and humanities. Based on these results, the authors offer recommendations for instructors and campus leaders, including improving CEJ visibility in course catalogs, strengthening CEJ integration within STEM and computer science, expanding initiatives and training focused on community engagement, and formally recognizing the contributions of community partners through instructional titles.

AbstractAlthough social networking sites (SNS) have been widely investigated, very limited information is available about how teachers navigate them within a fully online learning space, the challenges they confront, and the strategies they use to overcome them. Thus, we examined these underexplored areas by interviewing 14 higher education teachers in the field of social sciences. Using a cross-case analysis, overall data indicates that teachers had varied reasons for and considered different factors when adopting SNS for online teaching. Our study also reveals that they used SNS affordances depending on their own teaching contexts and took different roles when teaching online via this platform. Although teachers generally viewed SNS as an instructional approach, they also reported several technical, pedagogical, and learner-related challenges, which they attempted to confront using a variety of strategies. These findings confirmed that teachers’ pedagogical practices and decisions in an SNS-mediated learning environment are shaped by the interaction between and among the teacher-related factors, SNS as an instructional tool, and teaching goals mediated by the policies (existing or not) and their peers. Some key implications of our findings are on designing teacher development programs, recalibrating national, institutional, and classroom policies, and implementing a systemic approach to mitigating pedagogical challenges in an online learning space. Implications for future studies are also discussed.

AbstractThis research aims to address the current gaps in computer-assisted translation (CAT) courses offered in bachelor’s and master’s programmes in scientific and technical translation (STT). A multi-framework course design methodology is proposed to support CAT teachers from the computer engineering field, improve student engagement, and promote computer-supported education, together with a balanced coverage of the most relevant topics in the CAT domain. STT is currently in high demand in many fields, requiring translators with sector-specific language skills and considerable computer literacy in order to manage translation projects with complex structures, and format heterogeneity. However, many STT curricula often lag behind current market demands, focusing primarily on language and translation theory, with less emphasis on CAT technologies and tools. Moreover, the lack of shared course design guidelines hinders the introduction of innovative teaching approaches based on collaborative learning. A novel multi-framework CAT course design methodology, named CATDeM, is proposed, based on the integration between an official European translation competence framework, real-life-mimicking laboratorial activities, and computer-supported collaborative learning, enriched with discussion case studies and role-playing experiences. A real-life case study is examined to illustrate and evaluate the implementation of CATDeM in two consecutive editions (2020/2021 and 2021/2022) of a one-semester compulsory CAT course in a M.A. degree in STT at the University of Salento (Italy). Students’ perceptions of translation technology and role-plays, as well as their attitudes towards the proposed CAT course are evaluated through a post-grading self-assessment questionnaire. Achieved results indicated successful student engagement and self-assessed improvement in translation, technical, and interpersonal skills. The importance given by students to role-playing experiences mimicking professional scenarios was also highlighted, paving the way for CATDeM to be adopted in similar contexts.

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<strong>Abstract: </strong> The educational landscape of the 21st century is undergoing a transformative shift, primarily driven by the integration of artificial intelligence (AI) into learning environments. This paradigm shift, referred to as Artificially Intelligent Education, promises to redefine the traditional methodologies and approaches that have long characterized educational systems worldwide. At the core of this transformation is the capability of AI to provide personalized learning experiences, automate administrative tasks, and offer deep insights into student learning behaviours and needs. As AI technologies evolve, they bring forth a host of opportunities and challenges that educators, policymakers, and technologists must navigate to harness their potential effectively. This paper explores the impact of AI on education, highlighting the shift from a one-size-fits-all teaching model to a more tailored and adaptive learning framework. AI-enhanced educational tools and platforms are revolutionizing the ways in which content is delivered and consumed. Through adaptive learning technologies, AI can analyse a student's previous interactions and performance to tailor educational content to suit their individual learning pace and style. This approach not only improves engagement but also enhances comprehension and retention of knowledge. Moreover, AI-driven analytics enable educators to gain unprecedented insights into student progress and areas needing improvement, allowing for timely intervention and support. Additionally, AI facilitates a more inclusive learning environment by providing customized resources that cater to diverse learning needs, including those of students with disabilities. This paper details the development of various AI tools that contribute to these personalized learning experiences and discusses their implications for student outcomes and educational equity.However, the integration of AI into education is not without its challenges. Ethical considerations, such as data privacy, bias in AI algorithms, and the digital divide, pose significant hurdles that could undermine the efficacy and fairness of AI-driven educational systems. Furthermore, there is a critical need for curricula and teacher training to evolve in step with these technological advances, ensuring that educators are equipped not only to use these tools effectively but also to critically assess their impact on educational outcomes. This paper concludes by proposing a framework for the responsible implementation of AI in education, emphasizing the importance of collaborative efforts among educators, technologists, and policymakers. By addressing the challenges and optimizing the opportunities presented by AI, the field of education can move towards a future where learning is more personalized, accessible, and aligned with the needs of the 21st-century learner. <strong>Keywords:</strong> Artificial Intelligence (AI), Personalized Learning, Educational Technology, Ethical Considerations, Adaptive Learning Technologies <strong>Received - </strong>20/01/2024, <strong>Accepted </strong>- 27/01/2024, <strong>Published Date </strong>- 31/01/2024 &nbsp; &nbsp; &nbsp; &nbsp; <strong>&nbsp;</strong> <strong>Introduction to AI in Education</strong> Artificial Intelligence (AI) encompasses a broad range of technologies designed to emulate human cognitive functions such as learning, reasoning, problem-solving, perception, and language understanding. In the context of education, these technologies are primarily implemented through machine learning algorithms, natural language processing (NLP), and intelligent tutoring systems. Machine learning enables AI systems to improve their performance over time without being explicitly programmed by using large amounts of data. NLP allows computers to understand and interact with humans in natural language, facilitating AI applications like chat bots and virtual assistants that can aid in the learning process. Intelligent tutoring systems adaptively respond to individual student's needs, providing personalized instructions and feedback. Together, these technologies aim to enhance educational experiences and improve learning outcomes by offering more adaptive, responsive, and engaging educational tools. The integration of AI in education traces back several decades, with initial developments focused on simple computer-assisted instructions and adaptive learning systems. The 1980s and 1990s saw the emergence of early intelligent tutoring systems, such as the SCHOLAR and GUIDON systems, which used rule-based AI to teach and provide feedback in specific domains like medicine and biology. However, these systems were often limited in scope and adaptability. In recent years, the advancement of deep learning and the exponential increase in data availability and computing power have led to significant breakthroughs in AI capabilities. &nbsp; Today, AI is used in various educational applications from primary to tertiary and continuing education. Tools such as personalized learning platforms that adapt to individual learning speeds and styles, AI-driven data analytics for assessing student performances and educational outcomes, and AI-powered educational games and simulations are becoming increasingly commonplace. These tools are not only enhancing how content is delivered but are also providing educators with robust tools to measure and enhance their teaching effectiveness. &nbsp; Currently, the educational sector is witnessing a growing integration of AI technologies aimed at not only automating administrative tasks but also significantly enhancing instructional methods and learning environments. The proliferations of AI in education has facilitated remote learning and massively open online courses (MOOCs), which have broadened access to quality education, especially during the global challenges such as the COVID-19 pandemic. Despite these advancements, the field continues to face challenges related to ethical concerns, the need for massive data sets for AI training, and the digital divide that may limit access to AI-enhanced education for underserved populations. These areas present ongoing research and policy-making opportunities to optimize the benefits of AI in education while mitigating its risks. <strong>Personalization through AI</strong> Artificial intelligence (AI) has the potential to revolutionize the educational landscape by providing personalized learning experiences that cater to the unique needs of each student. At the core of this transformation is AI&rsquo;s ability to analyse vast amounts of data regarding a student&rsquo;s performance, learning habits, and preferences. AI systems can identify patterns and learning gaps that may not be evident at a glance. For example, through adaptive learning technologies, AI can determine if a student excels in visuallearning over textual or auditory methods. It can adjust the content delivery accordingly, offering more diagrams and videos for visual learners, detailed readings for textual learners, or podcasts and discussions for auditory learners. This adaptive approach helps in tailoring the educational experience to optimize student engagement and comprehension. AI can continuously monitor the progress of each learner and dynamically adjust the difficulty level and pace of the curriculum. Such systems use algorithms that assess a student&rsquo;s responses to various learning activities and automatically provide additional practice or advance to more challenging materials as needed. This is particularly beneficial in large classrooms where teachers may not always have the time to give detailed, individual attention to every student. AI-driven platforms can serve as an assistant that provides real-time feedback and support, helping students stay on track and achieve their learning goals more effectively. AI can also facilitate personalized learning paths. It can analyse a student&rsquo;s long-term academic performance and recommend career paths or future courses that align with their demonstrated skills and interests. For instance, a student showing strong aptitude in mathematical reasoning and analytical skills might receive suggestions to explore advanced mathematics, statistics, or computer science courses. This level of guidance is pivotal in helping students make informed decisions about their educational and professional futures, enhancing motivation and relevance in their studies. AI&rsquo;s role in education extends to supporting educators by providing them with detailed insights into each student&rsquo;s learning process. This allows teachers to make informed decisions about how to structure their instruction to meet the needs of diverse learners effectively. For instance, AI-generated reports can highlight which students need more help on specific topics, who might benefit from accelerated content, or what collective misconceptions need to be addressed in class discussions. By leveraging AI, educators can focus more on pedagogy and less on the logistics of content delivery, creating a more efficient and effective educational environment that prioritizes individual student needs and outcomes.The integration of AI in personalized learning leverages machine learning algorithms and data analytics to deliver educational experiences that are tailored to the individual needs and abilities of each student. This approach fundamentally changes the learning landscape by using AI to assess each student's current knowledge base, learning pace, and preferred learning styles. AI systems analyse these parameters and continually adjust the content difficulty, feedback, and instructional methods accordingly. This dynamic adaptation helps to keep the learning process engaging and effective, maximizing student motivation and ensuring that each learner can achieve their potential.AI in personalized learning also encompasses the ability to predict student performance and identify potential learning gaps before they become problematic. Through the use of predictive analytics, AI can forecast which areas students might struggle with and provide pre-emptive interventions. This proactive approach helps in maintaining a continuous learning progression and supports educators in delivering targeted assistance. It minimizes frustration for learners by addressing challenges at their roots, providing a more seamless and supportive educational journey. AI-driven personalized learning can bridge the gap between students and educational content across diverse backgrounds and learning abilities. It can democratize learning by offering high-quality, customized education to students regardless of geographical and socio-economic boundaries. AI systems can deliver personalized learning experiences to a vast number of students simultaneously, making advanced education more accessible and inclusive. This broad reach, combined with the capacity for customization, underlines the transformative potential of AI in education, promising a future where learning is optimized for each individual's unique needs and potentials. <strong>AI and Curriculum Development</strong> The role of Artificial Intelligence (AI) in designing and updating curriculum is becoming increasingly significant as educational institutions seek more adaptive and personalized learning experiences for students. AI can analyse vast amounts of educational data to identify trends, gaps, and opportunities in existing curricula. For example, by evaluating student performance across various subjects and levels, AI systems can help educators understand which areas are most challenging for students and require enhanced instructional focus. Additionally, AI can track the evolution of job markets and emerging technological trends, ensuring that the curriculum remains relevant and prepares students effectively for future careers. AI also plays a crucial role in the personalization of education. It allows for the development of dynamic curricula that adapt to the learning pace and style of individual students. AI-powered platforms can suggest custom learning paths and resources, modify difficulty levels in real time, and provide targeted interventions based on real-time feedback and assessment data. This level of personalization is not feasible at scale without AI, as it requires constant adjustment and fine-tuning of the learning content and methodologies to meet each student's unique needs and capabilities. AI assists in the continuous updating of curricula by automating the collection and analysis of feedback from various stakeholders, including students, teachers, and industry experts. This ongoing process helps in identifying which parts of the curriculum are outdated or less effective. AI-driven analytics can highlight the need for new courses or updates faster than traditional methods, supporting academic institutions in keeping their courses fresh and in alignment with both academic advancements and industry requirements. By facilitating a more responsive and agile curriculum development process, AI ensures that educational content not only meets current standards but also anticipates future educational needs and job market trends. <strong>AI-Driven Assessment Tools</strong> The integration of Artificial Intelligence (AI) into educational systems, specifically for grading and providing feedback, is a rapidly evolving domain that holds promise for enhancing educational outcomes and operational efficiency. AI grading systems primarily utilize natural language processing (NLP) technologies to evaluate written responses and machine learning to adapt and improve over time. These systems can handle large volumes of work in a fraction of the time required by human graders, thereby reducing workload and providing immediate feedback to students. This swift feedback can be particularly beneficial in large classes or online courses, where the scale might otherwise delay responses. However, the use of AI in grading is not without its challenges and limitations. One significant concern is the potential for AI to misunderstand nuanced or creatively structured answers. AI systems are typically trained on datasets that may not fully encapsulate the diversity of expression found in student work. Consequently, there's a risk of migrating or failing to appreciate unique, correct responses that deviate from expected patterns. Furthermore, students might learn to 'game the system' by tailoring their answers in ways that are more likely to be rewarded by algorithms, potentially stunting genuine learning and critical thinking skills. The ethical considerations are also paramount when deploying AI in education. Issues around privacy, data security, and bias need careful examination. AI systems can inadvertently perpetuate and amplify biases present in their training data, leading to unfair outcomes for certain groups of students. Additionally, reliance on digital tools raises concerns about data privacy and the security of student information, especially when third-party providers are involved in the AI systems' development and maintenance. The potential for AI to transform educational assessment is undeniable. When used responsibly and as a complement to human oversight, AI can offer more personalized, timely, and detailed feedback than would otherwise be possible, particularly in under-resourced educational environments. To maximize the benefits while mitigating risks, educational institutions should focus on transparent, inclusive, and ethically responsible AI implementation strategies. This includes rigorous validation of AI systems for accuracy and fairness, regular reviews by human educators, and clear communication with students about how their work is being assessed. With careful management, AI in grading can serve as a valuable tool to enhance educational delivery and student learning outcomes. AI-driven assessment tools have significantly transformed the landscape of both educational and professional environments by offering scalable, efficient, and consistent ways to evaluate knowledge, skills, and abilities. These tools utilize algorithms to grade and provide feedback on a wide range of assessments, from standardized testing to more complex analytical tasks. One of the primary benefits of such technology is its ability to deliver immediate feedback, a feature particularly useful in educational settings where timely feedback is crucial for effective learning. Moreover, these systems can handle large volumes of assessments simultaneously, which reduces the time and labour traditionally associated with grading, thereby allowing educators and professionals more time to focus on curriculum development and training activities. AI-driven assessment tools also bring a significant degree of personalization to the evaluation process. By analysing large sets of data, these tools can adapt to the individual learning pace and style of each student, potentially identifying strengths and weaknesses that may not be evident through traditional assessment methods. For instance, adaptive testing can modify the difficulty of questions based on the examinee's previous responses, offering a tailored assessment experience that can more accurately measure a student&rsquo;s true capabilities and learning progress. There are several challenges associated with the use of AI in assessments. One major concern is the potential for bias in AI algorithms, which can occur due to biased training data or flawed algorithm design. This can lead to unfair assessments and outcomes that disproportionately affect certain groups of people, thereby undermining the fairness and credibility of these tools. Additionally, over-reliance on automated systems may neglect the development of critical thinking and problem-solving skills, as these systems are typically optimized for quantifiable outcomes and may not effectively assess more nuanced skills such as creativity and interpersonal abilities. The implementation of AI-driven assessment tools raises significant concerns regarding data privacy and security. The collection and analysis of large amounts of personal and performance data necessitate robust protections to prevent data breaches and ensure that individuals&rsquo; privacy is respected. This challenge is compounded by the varying regulations and standards across different regions, which can make it difficult for institutions to implement these tools universally. In conclusion, while AI-driven assessment tools offer substantial benefits in terms of efficiency and personalization, they also present notable challenges that must be addressed to ensure their fair, effective, and secure use in both educational and professional settings. AI-driven assessment tools differ from traditional assessment methods in several key ways, each carrying its own advantages and challenges. Traditional assessments, which often include paper-based tests, essays, and oral examinations, have long been the standard in educational and professional environments. These methods rely heavily on human judgment for scoring and feedback, which can introduce a high level of subjectivity and potential for inconsistency. One of the primary distinctions is the scalability and efficiency offered by AI-driven tools. Traditional methods are labour-intensive, requiring significant time from educators or examiners to prepare, administer, and grade. This process is not only slow but can also be prone to human error and bias, particularly in subjective assessments like essays or presentations. In contrast, AI systems can process and evaluate large volumes of assessments quickly and consistently, without fatigue, thereby providing more uniform outcomes. Another significant advantage of AI-driven assessments over traditional methods is the ability to offer personalized and adaptive testing experiences. Traditional assessments are typically static, offering the same questions to every test-taker, which can fail to account for varying skill levels and learning paces. AI-driven tools, however, can adjust the difficulty of questions in real-time based on an individual's previous responses, allowing for a more tailored assessment that can more accurately reflect an individual's knowledge and abilities. This can lead to a more efficient assessment process, as it can potentially reduce the number of questions needed to accurately knowledge a student&rsquo;s competency. Traditional methods have advantages in assessing more complex cognitive and interpersonal skills. For example, oral exams and in-person presentations can better gauge a student's communication skills, critical thinking, and ability to interact in real-world scenarios. AI assessments, while improving, often struggle to accurately assess these more nuanced skills, which are crucial in many academic and professional fields. Additionally, traditional assessments involve direct human interaction, which can provide immediate contextual feedback in a more personalized and empathetic manner. AI-driven assessments provide remarkable scalability, efficiency, and personalization, traditional assessment methods still hold significant value in evaluating complex human skills and offering a more nuanced and interactive assessment experience. The choice between AI-driven and traditional assessments may depend on the specific needs of the educational or professional program and the skills it aims to measure. <strong>Enhancing Engagement with AI</strong> AI technology significantly enhances student engagement through personalized learning environments and interactive content. Personalized learning platforms use AI to analyse individual performance data and preferences, allowing the system to tailor the difficulty and types of tasks presented to each student. This approach ensures that thelearning process is aligned with the student&rsquo;s pace and interest, thereby maximizing engagement and effectiveness. Additionally, AI-driven gasification incorporates elements like points, badges, and leader boards tailored to each user's achievements, making learning a more fun and competitive experience. These platforms can dynamically adjust challenges based on a student&rsquo;s interactions, ensuring the content remains engaging and not overly daunting. AI is instrumental in providing real-time support and predictive insights through chat bots and virtual assistants. These AI tools offer instant academic help and guidance, facilitating a continuous learning process without delays. They can also detect subtle changes in student engagement and adapt their interaction accordingly, which helps in maintaining an active learning environment. Moreover, AI applications in creating adaptive content such as simulations and interactive videos cater to different learning styles, keeping students actively involved by providing hands-on, responsive experiences that adjust based on real-time student input and actions. Through these innovative applications, AI technologies foster an engaging, personalized, and supportive learning atmosphere that can lead to improved educational outcomes. AI-driven gamification and interactive learning environments are transforming the way educational content is delivered, making learning more engaging and personalized. In gamification, AI is utilized to create adaptive learning paths where the challenges and rewards are customized to the learner's skill level and progress. For instance, a language learning app might use AI to analyse a student's previous answers and tailor future quizzes to areas that need improvement, all while incorporating game-like elements such as points, levels, and badges to motivate the learner. Additionally, AI can dynamically adjust the difficulty of tasks in real-time to keep the learner in a state of flow, where the activity is neither too easy nor too challenging, fostering an optimal learning environment. In interactive learning environments, AI enhances interactivity and immersion through virtual and augmented reality systems. For example, a virtual lab simulation for chemistry students can use AI to simulate complex experiments that react differently depending on the student's input, mimicking a real-world lab experience. AI can also facilitate role-playing scenarios in which students interact with AI-driven characters, allowing them to practice language skills or medical procedures in a risk-free setting. Such environments leverage AI's capability to process natural language and understand user input, thereby providing immediate feedback and adapting the scenario to enhance the learning experience. This not only makes learning more interactive but also deeply engaging, promoting better retention of knowledge and skills. <strong>AI in Classroom Management</strong> AI tools are increasingly becoming integral in assisting teachers with managing classroom activities, enhancing both the effectiveness of teaching and the efficiency of administrative tasks. These tools can automate routine tasks such as attendance taking, grading, and scheduling, freeing up teachers to focus more on instructional time and student interaction. AI-driven platforms can also facilitate personalized learning by tracking student performance and adapting curriculum to meet individual needs. This personalized approach helps in identifying students who may be struggling or those who need more challenging material, ensuring that all students receive the appropriate level of support and challenge. AI tools help in creating a more engaged learning environment through the use of interactive and adaptive learning technologies. Educational software and applications powered by AI can provide students with interactive simulations, educational games, and problem-solving activities that are designed to enhance learning outcomes and keep students motivated. These tools often include real-time feedback mechanisms, allowing students to understand their mistakes and learn from them immediately, which can significantly enhance the learning process. For teachers, this means a more dynamic classroom where instruction is supported by tools that adapt to the educational needs of students in real-time. AI can assist in managing communication within the classroom setting. Tools such as AI-powered chat bots can answer students&rsquo; frequently asked questions and assist with homework outside of school hours. This provides students with continuous support and can help maintain their interest and engagement with the subject matter. In a broader sense, AI can also analyse communication patterns and provide teachers with insights into how to improve interactions or identify issues that might be affecting classroom dynamics. Overall, AI tools not only support the administrative and instructional aspects of teaching but also enhance interaction and communication, leading to a more effective and cohesive educational environment. The integration of artificial intelligence (AI) into classroom management has shown significant potential to reduce teacher workload and enhance efficiency. AI-driven tools can automate routine administrative tasks such as attendance taking, grading, and scheduling, allowing teachers to devote more time to instructional activities and personalized student engagement. Moreover, AI can analyse data on student performance and classroom behaviour, providing teachers with actionable insights. This data-driven approach helps in identifying students' learning patterns, predicting areas where students may struggle, and tailoring educational interventions accordingly. As a result, teachers are better equipped to address diverse learning needs efficiently, enhancing overall classroom effectiveness. AI can streamline communication between teachers, students, and parents, ensuring that all stakeholders are well-informed and actively involved in the educational process. Platforms that utilize AI can help in managing communications, sending out reminders for assignments, and even providing initial responses to common student inquiries, thus reducing the manual effort required from teachers. This increased efficiency not only reduces the stress associated with teacher workload but also improves the quality of education by enabling a more organized and responsive teaching environment. Overall, the deployment of AI in classroom management promises a more sustainable and dynamic educational ecosystem, potentially leading to improved educational outcomes and a better work-life balance for teachers. <strong>Predictive Analytics in Education</strong> The use of artificial intelligence (AI) to predict student performance and dropout rates is an emerging field that leverages machine learning algorithms to analyse various data points about students and their learning environments. These algorithms are trained on historical data such as grades, attendance records, socio-economic background, engagement levels in class activities, and many other factors that could influence a student's success in school. By identifying patterns and trends within this data, AI can predict which students are at risk of underperforming or dropping out. This predictive capability enables educational institutions to intervene proactively, offering targeted support and resources to students who need it most. It also helps in optimizing resource allocation, designing personalized education plans, and improving overall educational outcomes. The implementation of AI in predicting student outcomes poses both opportunities and challenges. It allows educators to understand the complex interplay of factors that affect student success at a granular level, potentially transforming how educational policies and practices are designed. However, it also raises concerns about privacy, data security, and the ethical use of predictive information. Moreover, there is a risk of perpetuating existing biases if the AI systems are trained on skewed or biased data sets. Therefore, while AI can significantly enhance educational strategies by providing detailed insights into student performance, it is crucial that these technologies are developed and implemented thoughtfully and inclusively, with an ongoing evaluation of their impact and effectiveness. In the context of education, the application of artificial intelligence (AI) for strategic interventions based on predictive insights represents a transformative shift towards personalized and efficient learning environments. AI-driven analytics can mine extensive data sets&mdash;ranging from student interaction logs, performance records, and demographic information&mdash;to identify patterns and predict student outcomes. This predictive capability allows educators and administrators to implement proactive strategies tailored to the needs of individual students or specific groups. For example, AI can help in predicting which students might struggle with certain subjects, enabling early interventions such as customized tutoring sessions or specialized content delivery that can help bridge knowledge gaps before they widen. AI in education extends to optimizing curriculum development and resource allocation, enhancing the overall learning experience. By analysing trends over time, AI systems can recommend adjustments to teaching methodologies, suggest the most effective multimedia tools, or even adapt the pace of content delivery to suit diverse learning speeds. This level of customization ensures that educational institutions can better serve their student populations, promoting higher engagement and achievement rates. Strategic interventions powered by AI not only focus on academic performance but also incorporate socio-emotional factors, aiming to build a supportive learning environment that anticipates and addresses educational challenges in a holistic manner. This integration of AI fosters a more inclusive, adaptive, and forward-thinking educational landscape. <strong>Ethical Considerations in AI-Driven Education</strong> AI-driven education brings with it a myriad of ethical challenges that educators, developers, and policymakers must navigate carefully. One of the primary concerns is privacy. As AI systems often require large volumes of data to function optimally, the collection, storage, and processing of student data&mdash;including potentially sensitive information related to learning patterns, behavioural traits, and personal demographics&mdash;pose significant privacy risks. There is a critical need to establish stringent data protection measures and ensure that data collection is transparent and consensual. Additionally, the integration of AI in education raises questions about the extent of surveillance in learning environments and the impact it may have on student autonomy and trust. Another set of ethical challenges revolves around bias and accountability. AI systems can inadvertently perpetuate and amplify existing biases if they are trained on skewed or unrepresentative data sets. This can lead to unfair treatment of students based on race, gender, socioeconomic status, or other factors, thereby reinforcing existing inequalities in educational outcomes. Addressing this requires not only careful design and training of AI models to ensure fairness and inclusivity but also ongoing monitoring to detect and correct bias as it arises. Furthermore, accountability is crucial in AI-driven education; it must be clear who is responsible for the decisions made by AI systems. This includes determining who is accountable when an AI makes an error that negatively affects a student's learning progress or outcomes. Ensuring that there are mechanisms for human oversight and intervention in AI-driven systems is essential to maintain trust and effectiveness in educational settings. Transparency and explain ability must be prioritized. Educational institutions should be transparent about the AI systems they deploy, including the types of data these systems utilize, how they process this data, and the purpose for which it is used. It&rsquo;s crucial that both students and educators understand how AI decisions are made, particularly when these affect student assessments, personalized learning paths, or recommendations. Ensuring that AI systems are explainable and their outputs justifiable builds trust and accountability, making it easier for users to recognize and rectify biases or errors. Fairness and bias mitigation are critical. AI systems should be continuously monitored and audited to detect and address any implicit biases that could affect student outcomes based on race, gender, socio-economic status, or disability. This involves training AI models on diverse data sets that accurately reflect the varied student population. Institutions should also implement regular reviews of AI outcomes to ensure equitable impacts across all student groups, adjusting the systems as needed to prevent discrimination and to promote inclusivity. Data privacy and security practices must be stringent. Educational institutions must comply with local and international data protection laws, such as GDPR in Europe or FERPA in the United States, ensuring that student data is handled securely and with consent. Students and parents should have clear options to opt out of data collection or AI analysis where feasible, and they should be informed of the potential implications of these technologies on the student's educational experience. Strong encryption methods, secure data storage solutions, and regular security audits should be standard to protect sensitive information from unauthorized access or breaches. <strong>AI, Accessibility, and Inclusivity</strong> Artificial Intelligence (AI) is significantly enhancing the accessibility of education for students with disabilities by providing customized learning experiences and removing barriers that traditional educational methods often present. For instance, AI-driven technologies such as text-to-speech and speech recognition tools are transformative for students with visual impairments or reading difficulties, enabling them to access textual content through auditory means. Additionally, AI can adapt learning materials to the needs of each student, allowing for variations in presentation that suit different learning styles and disabilities. Predictive analytics, another facet of AI, can help educators identify individual student needs early, allowing for timely intervention and support to ensure all students have equal opportunities to succeed in their educational endeavours. AI facilitates real-time communication and interaction adjustments, which are critical for students with hearing impairments or cognitive disabilities. Through AI-powered apps and platforms, these students can receive instant subtitles for spoken words or complex instructions broken down into simpler, manageable steps. This technology also extends to sign language recognition systems that convert sign language into text, making classroom interactions more inclusive. By automating and customizing the delivery of educational content, AI helps create a learning environment that acknowledges and adjusts to the unique challenges faced by students with disabilities, thus fostering a more inclusive education system where barriers to learning are continuously identified and addressed. Inclusive education, aimed at supporting diverse student needs within a mainstream educational setting, has been significantly enhanced through the application of Artificial Intelligence (AI). One prominent example involves AI-powered tools like text-to-speech and speech recognition technologies, which have been transformative for students with visual impairments and learning disabilities such as dyslexia. For instance, platforms integrating AI-driven algorithms can customize learning experiences, adapting content to suitable formats and providing personalized learning pathways. Such tools not only enhance reading and comprehension skills by converting text to audio but also allow students to interact with the content through verbal commands, thereby promoting independence and engagement in the learning process. Another case study centres around the use of AI to support students with autism spectrum disorders (ASD). AI technologies, including machine learning models and robotics, have been utilized to develop social robots that assist in teaching social and communication skills to autistic students. These robots engage students through consistent, repeatable, and patient interaction, which can be less intimidating than human interactions for some individuals with ASD. Additionally, AI-driven data analysis tools help educators identify unique learning patterns and potential hurdles specific to each student, enabling tailored educational strategies that accommodate individual learning speeds and styles. Through these applications, AI facilitates a more inclusive educational environment where students with diverse needs receive the support necessary to thrive academically and socially. <strong>Preparing for the Future</strong> As artificial intelligence (AI) becomes increasingly integrated into various aspects of daily life and work, students need to develop specific skills to thrive in this new landscape. Digital literacy is crucial; this includes not only the ability to use technology but also to understand the basics of how AI systems work, the data they use, and their limitations. Critical thinking skills are also essential, allowing students to discern the quality of information generated by AI and make informed decisions based on its output. As AI automates routine tasks, creativity and innovation become invaluable skills, enabling students to identify and solve complex problems where human intuition and novel thinking are irreplaceable. Additionally, interpersonal and ethical skills will play a significant role in a future dominated by AI technologies. Emotional intelligence, the capacity to be aware of, control, and express one's emotions, and to handle interpersonal relationships judiciously and empathetically, will be vital as machines lack these nuanced human capabilities. Understanding and navigating ethical considerations in the use of AI, such as bias, privacy, and accountability, will be crucial. These competencies ensure that students can use AI responsibly and effectively, fostering environments where technology serves to enhance human capabilities and quality of life rather than diminishing them. Educational systems around the world are increasingly recognizing the importance of adapting curricula and teaching methods to prepare students for a future job market that is expected to be heavily influenced by artificial intelligence (AI) and technology. To this end, there is a growing emphasis on STEM (Science, Technology, Engineering, and Mathematics) education, as these areas are foundational to understanding and working with AI. Schools and universities are incorporating more computer science classes, including programming, data analysis, and specific courses on AI and machine learning. Beyond STEM, there is also a push to integrate these technologies across all subjects to foster a deeper understanding of how AI can be applied in various fields, thereby encouraging a more interdisciplinary approach to education. Additionally, to equip students with the necessary skills for future jobs, educational systems are also focusing on developing soft skills such as critical thinking, creativity, and problem-solving. AI is expected to automate many routine tasks, so these higher-order thinking skills are becoming crucial. Schools are incorporating project-based learning and collaborative assignments to help students develop these skills. Furthermore, there is an emphasis on lifelong learning and adaptability, recognizing that the rapid pace of technological change will require continuous skill development and re-skilling throughout one&rsquo;s career. Educational technologies, including AI-driven personalized learning platforms, are being utilized to support tailored educational experiences that meet individual learning styles and pace, thereby enhancing student engagement and effectiveness of the learning process. <strong>Challenges and Limitations of AI in Education</strong> <strong><u>Technical Challenges:</u></strong> The implementation of AI in any field, including education, faces significant technical challenges. One of the primary issues is the development of robust and scalable AI systems that can reliably process and interpret the vast amounts of data they receive. This involves not only the creation of powerful algorithms but also ensuring these systems can operate efficiently across diverse hardware and software environments. Another technical hurdle is the integration of AI tools with existing educational technologies, which may not always be straightforward. This integration requires careful planning and coordination to ensure data compatibility and functional interoperability, which are essential for a seamless user experience. <strong><u>Ethical Challenges:</u></strong> Ethical considerations are paramount in the deployment of AI in education. Issues of data privacy and security are at the forefront, as educational AI systems handle sensitive information about students' personal details, learning patterns, and academic performance. Ensuring that this data is protected and that students' privacy is respected is a major concern. Additionally, there is the risk of bias in AI algorithms, which can perpetuate or exacerbate existing inequalities if not carefully managed. AI systems must be designed to be as neutral as possible, with continuous monitoring and adjustments to mitigate any form of bias that might occur. <strong><u>Practical Challenges:</u></strong> On the practical side, the implementation of AI in education requires significant investment in both technology and training. Schools and educational institutions may face budget constraints that limit their ability to deploy AI solutions. There is also the challenge of digital literacy among educators and students, which can hinder the effective use of AI tools. Educators need to be trained not just to use these tools, but also to understand their capabilities and limitations. This training must be ongoing to keep pace with technological advancements. Moreover, there is the issue of ensuring that AI does not replace the human touch that is crucial in education but instead acts as a supplement to enhance the teaching and learning process. <strong>Balancing Challenges and Opportunities:</strong> Despite these challenges, the potential benefits of AI in education can be transformative, making it worth the effort to address these issues. By tackling the technical, ethical, and practical challenges head-on, stakeholders can pave the way for AI to enhance educational outcomes through personalization, efficiency, and accessibility. Collaborative efforts among educators, technologists, policymakers, and the community are essential to develop strategies that maximize the benefits of AI while minimizing its risks. Through responsible implementation, AI can significantly contribute to preparing students for the demands of the 21st-century world. <strong>Limitations of current AI technologies in addressing complex educational needs</strong> The integration of Artificial Intelligence (AI) in education has been met with much enthusiasm, attributed to its potential to revolutionize how educational content is delivered, personalized, and assessed. However, as with any technological advancement, AI in education comes with a set of significant limitations that must be addressed to fully realize its benefits while mitigating negative impacts. <strong>1. Emotional and Social Intelligence Deficits:</strong> One of the primary limitations of AI in educational settings is its inability to mimic the emotional and social intelligence of human teachers. AI systems can tailor learning paths based on cognitive data and performance metrics, but they lack the capacity to sense, respond to, or appreciate the emotional states of students. Effective education is not merely about knowledge acquisition; it involves understanding student emotions, which can significantly affect motivation and engagement. Human teachers can perceive when a student is struggling not just intellectually but emotionally&mdash;be it stress, confusion, or disinterest&mdash;and can intervene in ways that are supportive and empathetic. AI, however, is not equipped to handle such nuances, which can lead to a learning experience that feels impersonal and detached. <strong>2. Inherent Biases in AI Systems:</strong> AI-driven educational tools rely heavily on data to make decisions or recommendations. If the underlying data is biased or not representative of the diverse student populations, the AI's outputs will inevitably inherit these biases. This can manifest in several detrimental ways, such as favouring one demographic over another or failing to accommodate the unique needs of students from varied backgrounds. For instance, an AI system developed predominantly with data from urban, well-funded schools may not perform effectively for students in rural or underfunded schools, exacerbating existing educational inequalities rather than alleviating them. <strong>3. The Irreplaceability of Human Interaction:</strong> The role of a teacher is profoundly complex, extending beyond the delivery of curriculum content to include mentorship, motivation, and the fostering of a safe and conducive learning environment. Teachers inspire, lead by example, and cultivate a sense of curiosity and a desire to learn. While AI can efficiently manage information dissemination and conduct assessments, it cannot replicate the mentor-student relationship that is vital for educational and personal growth. Human teachers also play a critical role in fostering group interactions and promoting social skills among students&mdash;areas where AI applications fall short. <strong>4. Ethical and Privacy Concerns with AI in Education:</strong> Deploying AI in educational settings raises significant ethical concerns, particularly regarding privacy and surveillance. AI systems often require the collection, storage, and processing of personal data, posing risks related to data breaches and misuse. Additionally, the continuous monitoring capabilities of AI could lead to an Orwellian scenario where every action of a student is watched, potentially infringing on privacy and impacting student behaviour. Educators and policymakers must tread carefully to balance the benefits of AI technologies with the need to protect student rights and freedoms. <strong>5. Technological Access and Inequality:</strong> The efficacy of AI in education is heavily dependent on the availability of suitable technological infrastructure. This includes not only access to computers and other devices but also to reliable, high-speed internet. Disparities in access to technology&mdash;often along socio-economic and geographical lines&mdash;can lead to a digital divide where some students benefit from AI-enhanced education while others are left behind. This technological inequality can lead to widening gaps in educational achievements between different groups of students. <strong>6. Challenges in Developing Critical and Creative Thinking:</strong> AI in education is often geared towards optimizing the learning process through structured tasks and feedback systems. However, this focus can neglect the development of critical and creative thinking skills, which are crucial for students to effectively navigate the complexities of the real world. Education should involve open-ended questions and unstructured problems that foster innovation and critical analysis&mdash;areas where AI's structured and algorithmic nature may not provide the best support. <strong>7. Resistance to Technological Integration:</strong> The adoption of AI in educational contexts also faces practical challenges, including resistance from educators, students, and parents. Teachers might view AI tools as a threat to their professional autonomy or fear being replaced by technology. Additionally, there might be scepticism regarding the effectiveness of AI in improving educational outcomes. Effective integration of AI requires addressing these concerns through transparent communication, demonstrating the value added by AI, and ensuring that these tools support rather than replace the human elements of teaching. To address these limitations, a nuanced approach that emphasizes the complementary role of AI in education is essential. By leveraging AI to handle certain tasks while ensuring that the core of teaching remains human-cantered, the educational landscape can evolve in a way that harnesses the best of both worlds. <strong>Future Trends and Innovations in AI and Education</strong> Emerging technologies, particularly in the realm of artificial intelligence (AI), are set to significantly reshape the educational sector by enhancing both teaching methodologies and learning experiences. Adaptive learning technologies, which are one of the forefront applications of AI, exemplify this shift. These systems utilize AI to assess the abilities and learning progress of individual students in real-time, adjusting the content difficulty, style, and pacing according to each student&rsquo;s unique needs. This personalized approach aims to maximize learning efficiency and engagement by ensuring that each student faces challenges tailored to their current level, potentially boosting their academic performance and interest in the subject matter. Another profound impact of AI in education is seen through Intelligent Tutoring Systems (ITS). These systems create a close-to-personal tutoring experience, where the machine responds to student inquiries, provides customized feedback, and explains concepts in varied ways until the learner gains a proper understanding. This technology is particularly revolutionary in environments where there is a shortage of qualified teachers, as it offers a scalable method to deliver high-quality, personalized education, and maintains learning continuity in diverse settings. AI is streamlining administrative tasks in education through automated grading systems. These systems are not limited to objective assessments like quizzes but are increasingly capable of evaluating subjective answers and essays. The implementation of such technology can significantly reduce the grading workload on educators, allowing them more time to focus on instructional design and student interaction. Furthermore, the instant feedback provided by automated systems can be crucial for the learning process, offering students timely insights into their understanding and areas for improvement. Virtual and Augmented Reality (VR/AR) technologies also complement AI in transforming educational landscapes by providing immersive learning environments. These technologies enable students to explore complex or abstract concepts in a highly interactive manner&mdash;for instance, VR can simulate historical events or distant planets, offering students a deeper, experiential form of learning that is often more engaging than traditional textbooks. When integrated with AI, these simulations can adapt to student interactions, providing customized learning experiences that respond to the user&rsquo;s input and learning style. However, the deployment of such technologies also requires careful consideration of ethical issues, particularly concerning data privacy and the risk of widening the digital divide. The effective use of AI in education hinges not only on technological advancements but also on ensuring equitable access and maintaining the human touch that is crucial in education. As these technologies continue to develop, they must be governed by policies that protect student data and ensure that the benefits of AI are accessible to all students, regardless of their socio-economic background. By navigating these challenges, AI can significantly enhance educational outcomes and herald a new era of personalized learning. As AI technology continues to evolve, its integration into educational settings is poised to transform how education is delivered, personalized, and managed. Looking towards the future, several predictions can be made about the role of AI in education, reflecting both the potential enhancements and the challenges to be navigated. AI is expected to drive significant advances in personalized learning. Algorithms capable of analysing individual learning patterns and preferences will make it possible to tailor educational content to the needs of each student. This means that the pacing, level of difficulty, and teaching styles can be adjusted to optimize each student&rsquo;s learning potential. This will not only help in accommodating diverse learning abilities within a single classroom but also assist in closing gaps in educational achievement. AI will likely automate many administrative tasks that currently consume substantial amounts of teachers&rsquo; time. Grading of quizzes, essays, and even participation can be handled by sophisticated AI systems, freeing educators to focus more on teaching and less on paperwork. Furthermore, AI could help in creating and updating curricula that are not only tailored to individual students but also adapt to changing societal needs and job markets, ensuring that educational content remains relevant and dynamic as AI becomes more embedded in educational tools, virtual and augmented reality will become more commonplace in classrooms. These technologies, enhanced by AI, will provide students with immersive learning experiences that are both engaging and effective. For instance, complex scientific concepts or historical events can be explored in virtual environments that make learning more tangible and impactful. This immersive technology can drastically enhance learning by making abstract or difficult content more accessible and interesting. However, with these advancements, there will also be significant challenges, particularly concerning data privacy and ethical considerations. As AI systems require large datasets to function optimally, the collection and handling of sensitive student information will need to be managed with strict adherence to privacy laws and ethical standards. Educators and technologists will need to work together to establish protocols that protect students and their personal information while enabling the benefits of AI. The future of AI in education will necessitate continuous professional development for educators. Teachers will need to become proficient not only in their subject areas but also in using advanced technologies that support AI-driven education. This will require substantial investment in teacher training and may also change the role of the teacher from a knowledge provider to a facilitator of learning experiences.In sum, while AI promises to enrich educational experiences significantly; its successful integration will depend on careful management of ethical issues, robust privacy protections, and ongoing support for educators. If these elements are effectively addressed, AI has the potential to revolutionize the educational landscape by making learning more personalized, efficient, and engaging. <strong>Conclusion</strong> The transformative potential of artificial intelligence (AI) in education is vast and multifaceted, offering possibilities that could redefine teaching and learning processes. AI can significantly enhance personalized learning, providing tailored educational experiences that meet the individual needs of each student. By analysing data on students&rsquo; learning styles, progress, and challenges, AI can adapt curriculum and instruction in real-time. For instance, intelligent tutoring systems can offer additional practice on topics a student struggles with, or suggest advanced content when a student is ready to move forward, ensuring optimal learning progression for everyone. AI can streamline administrative tasks that traditionally consume much of educators' time, thereby allowing teachers to focus more on teaching and less on logistics. Automation tools can handle grading, scheduling, and even communication with students and parents, making these processes more efficient and less prone to human error. This not only improves the efficiency of educational institutions but also enhances the quality of interaction between students and educators. Teachers can spend more time engaging with students in meaningful ways, facilitating deeper discussion, and addressing individual concerns more effectively. AI also holds promise for breaking down barriers in education, making quality learning materials and experiences accessible to a broader range of students, including those in remote or underserved areas. Through technologies such as AI-powered online learning platforms, students from around the world can access lectures, resources, and support from top-tier educational institutions. Moreover, AI can assist in language translation and content adaptation, which are crucial for non-native speakers and can democratize access to global educational content, fostering a more inclusive learning environment. However, the integration of AI in education also presents challenges and ethical considerations that must be addressed. Issues such as data privacy, security, and the potential for AI to perpetuate existing biases must be carefully managed. Educators and policymakers need to establish robust frameworks and guidelines to ensure that AI tools are used responsibly and that they truly enhance educational outcomes without compromising ethical standards or exacerbating inequalities. In conclusion, while AI&rsquo;s potential to transform education is undeniable, realizing this potential requires careful implementation, ongoing evaluation, and adaptive policy frameworks. As AI continues to evolve, it is imperative that educators and technologists collaborate closely to harness its capabilities in a way that enriches the learning experiences and prepares students effectively for the future. This collaborative approach can ensure that AI serves as a powerful tool for educational enrichment rather than a source of contention. &nbsp;

AbstractA major challenge in studying naturalistic vision lies in controlling stimulus and scene viewing time. This is especially the case for studies using real-world objects as stimuli (rather than computerized images) because real objects cannot be “onset” and “offset” in the same way that images can be. Since the late 1980s, one solution to this problem has been to have the observer wear electro-optic spectacles with computer-controlled liquid-crystal lenses that switch between transparent (“open”) and translucent (“closed”) states. Unfortunately, the commercially available glasses (PLATO Visual Occlusion Spectacles) command a high price tag, the hardware is fragile, and the glasses cannot be customized. This led us to explore how to manufacture liquid-crystal occlusion glasses in our own laboratory. Here, we share the products of our work by providing step-by-step instructions for researchers to design, build, operate, and test liquid-crystal glasses for use in experimental contexts. The glasses can be assembled with minimal technical knowledge using readily available components, and they can be customized for different populations and applications. The glasses are robust, and they can be produced at a fraction of the cost of commercial alternatives. Tests of reliability and temporal accuracy show that the performance of our laboratory prototype was comparable to that of the PLATO glasses. We discuss the results of our work with respect to implications for promoting rigor and reproducibility, potential use cases, comparisons with other liquid-crystal shutter glasses, and how users can find information regarding future updates and developments.

<strong>Gyeongsang University Turnitin Trash Files</strong> <strong>HUMAN CAPITAL NEXUS AND GROWTH OF NIGERIA ECONOMY</strong> <strong>CHAPTER ONE</strong> <strong>INTRODUCTION</strong> <strong>Background to the Study </strong> Government expenditure equally known as public spending simply refers to yearly expenditure by the public sector (government) in order to achieve some macroeconomic aims notably high literacy rate, skilled manpower, high standard of living, poverty alleviation, national productivity growth, and macro-economic stability. It is also expenditure by public authorities at various tiers of government to collectively cater for the social needs of the people. Generally, it has been revealed that public expenditure plays a key role in realizing economic growth. This is because providing good education to individuals is one of the principal avenues of improving human resource quality in any economy. From this perspective, advancing school enrolment may subsequently lead to economic growth. Therefore, education remains the effective way to subdue poverty, illiteracy, underfeeding and accelerate economic growth in the long-term. Much attention has been channeled towards clarifying the relationship between education and economic growth, and so, has led to series of studies by economists over the past 30 years. There is substantial literature to back the fact that correlation exists between the two. (Sylvie, 2018). In line with the views of Hadir and Lahrech (2015), the fact that humans are the most worthy assets remains undisputable in both developed and developing countries. Therefore efficiency in human resource management is pertinent if development must be realized. In this sense, the major gateway to development is adequate investment in human capital which may be described as an individual&rsquo;s potential economic value in terms of skills, knowledge, and other intangible assets. In order to realize the well-known macroeconomic objective of economic growth, Nigeria being a developing country embarked on some programs in the educational sector with the aim of boosting human capital development. However, these programs have only served as conduits for enriching the corrupt political elite. Given the high prospects of achieving economic growth in Nigeria and the place of human capital development in its actualization, education, therefore, remains a top priority for the Nigeria government as well as concerned researchers. Thus, this study is one among other concerned studies that will attempt to examine economic growth and human capital nexus in Nigeria through education variables. In particular, using education as a measure of human capital, it will attempt to explore the impact of education variables on the growth of Nigeria&rsquo;s economy. According to Wamboye, (2015), education makes way for vital knowledge, skills, techniques and information for individuals to function in family and society. Education can groom a set of educated leaders to take on jobs in government services, public and private firms, and domestic and foreign firms. The growth of education can provide all kinds of grooming that would foster literacy and basic skills. Though alternative investments in the economy could generate more growth, it must not deviate from the necessary contributions; economic as well as non-economic, that education can make and has made to expediting macroeconomic growth (Clark, 2015). Todaro and Smith in Clark (2015), likewise called attention to the fact that, extension of education lead to an increasingly gainful labor force and provide it with expanded information and abilities, and boost employment and income-earning avenues for educators, schools, and employees. Economic growth, proxied by Gross Domestic Product (GDP), gives numerous advantages which include increasing the general living standard of the masses as estimated by per capita pay (income), making the distribution of income simpler to accomplish, thus, shortening the time span needed to achieve the fundamental needs of man to a considerable majority of the masses. The main source of per capita yield (output) in any nation, regardless of whether it is advanced or developing, is really increment in &#39;human productivity&#39;. Per capita yield (output) growth is notwithstanding a significant aspect of economic prosperity (Abramowitz, 1981). For the most part, it has been uncovered that individuals are the most important source of productivity growth and economic prosperity. Technology and technological hardware are the results of human inventions and innovativeness. The suggestion of UNESCO, that 26% of yearly planned expenditure (budget) in developing nations should be dedicated to education has become intangible, particularly in Nigeria. Planned expenditure on education in Nigeria ranges from only 5%-7% of total planned expenditure. The impact of the above situation on the economic prosperity of the nation as it concerns human capital development, capacity building, infrastructural advancement, etc, is troubling. On this note, the necessity of a well-thought out plan for rectifying this unwanted situation can&#39;t be over stressed. &nbsp; <strong>1.2 Statement of the Problem </strong> Sikiru (2011) as cited in Ajibola (2016) rightly pointed out that the role of education in any economy is no longer business as usual because of the knowledge based globalized economy where productivity greatly depends on the quantity and quality of human resource, which itself largely depends on investment in education. Governments continue to increase spending on education with a view toward enhancing the standard of education, build human capacity and attainment of economic growth. Ironically, this effort by government is still a far cry of UNESCO&rsquo;s recommendation of 26% total annual budget to education, and so, has not yielded the expected results. Thus, researchers sought to understand the relationship between government expenditure on education and economic growth and how they influence each other. These researches on the above subject matter, have given rise to divergent school of thoughts. Over time, Nigeria has indicated willingness to develop&nbsp; education in order to curtail illiteracy and quicken national development. Anyway regardless of the irreproachable evidence that education is key to the improvement of the economy; there exists a wide loop-hole in accessibility, quality and fairness (equity) in education (Ayo, 2014). Empirically verifiable facts in recent years have indicated that the Nigeria&nbsp;education system has continuously turned-out graduates who overtime have defaulted in adapting to evolving techniques and methods of production; due to inadequate infrastructure, underfunding, poor learning aids, outmoded curriculum, dearth of research and development. This has resulted to drastic reduction in employment and the advent of capacity underutilization. This paper assesses growth of Nigeria economy in relation to government expenditure on education and school enrollment from 1981 to 2018. Frequent adjustments and changes in education system in Nigeria, points to the fact that, all is not well with the countries education system. Government have experimented 6-3-3-4, 9-3-4 systems of education, among others. Enrollment in schools forms the main part of investment in human capital in most of the world&rsquo;s societies (Schultz, 2002). There are several explanations concerning why improvement in scholastic quality is not forthcoming in Nigeria as regards the above subject matter. Researchers disagree on whether changes in education attainment levels alters economic growth rate in the long-term. &nbsp;&ldquo;In Nigeria, average public education expenditure to total government expenditure between 1981 and 2018 is 5.68 per cent. It ranged between 0.51 and 10.8 per cent during the period under review&rdquo; (CBN Statistical Bulletin, 2019). However, the major problem therefore, is that despite an increase in the numeric value of budgetary allocation to education in Nigeria over the years, they still fall short of 26 % UNESCO,S recommendation. For instance, 2014, 10.6%; 2015, 9.5%; 2016, 6.1%, 2017, 5.41%, 2018, 7.0% and 2019, 7.2% percent respectively of total annual budget to education. The statistics presented above indicates that investment in education has not produced the desired level of human capital and economic growth in Nigeria. These uncertainties as it relates to government expenditure on education, school enrollment and growth of Nigeria economy gave birth to this research work. Furthermore, most studies relating to the subject matter, conducted analysis on times series data without subjecting these data sets to structural breaks, thereby giving rise to spurious results and therefore, unreliable recommendations. For instance, unit root test with structural breaks were not employed in majority of these studies. <strong>1.3 Research Questions </strong> The issues raised above have provoked series of questions which this study attempts to provide answers. These questions include; i. To what extent does government expenditure on education affect growth of Nigeria economy? ii. To what extent does primary school enrollment affect growth of Nigeria economy? iii. To what extent does secondary school enrollment affect growth of Nigeria economy? iv. To what extent does tertiary school enrollment affect growth of Nigeria economy? <strong>1.4 Objectives of the Study </strong> The main objective of the study is to access the effect of government expenditure on education and growth of Nigeria economy. Specific objectives of the study are to; i. Access the effect of government expenditure on growth of Nigeria economy. ii. Access the effect of primary school enrollment on growth of Nigeria economy. iii. Access the effect of secondary school enrollment on growth of Nigeria economy. iv. Access the effect of tertiary school enrollment on growth of Nigeria economy. <strong>1.5 Hypotheses of the Study </strong> The following hypotheses were tested in this study. i. Government expenditure on education has no significant effect on growth of Nigeria economy. ii. Primary school enrollment has no significant effect on growth of Nigeria economy. iii. Secondary school enrollment has no significant effect on growth of Nigeria economy. iv. Tertiary school enrollment has no significant effect on growth of Nigeria economy. <strong>1.6 Scope of the Study </strong> The study covers the time series analysis of government expenditure on education, school enrolment; primary, secondary and tertiary, and growth of Nigeria economy from 1981 to 2018. Based on available data. Justification for this study is on the premise that, time series data used for the study is a current data on government expenditure on education, education enrolment and economic growth in Nigeria. This study used annual data for the period 1981-2018, collected from the CBN Statistical Bulletin (2019) and World Bank databank. Variables employed for the study include; Real GDP Per Capita, government expenditure on education, primary, secondary and tertiary school enrolment. <strong>1.7 Significance of the Study </strong> Models of economic growth provide useful predictions that inform decisions made by policy makers. Agreeing with policy options based on inaccurate research studies could undermine government intervention particularly in the education sector. A good perception of the interaction among investment in education, its outcome, school enrolment and economic growth is appropriate policy measure, guarantees human capital development. Thus, a representative model that take cognisance of inter-play among public education expenditure, school enrolment and growth of the economy will lead to adequate disbursement and utilization of government funds. The outcome of this research will serve as a tool for policy makers in the Ministries of Finance, Education and the National Planning Commission including regulatory agencies not mentioned here. It will also serve as a reference material for subsequent research work in this field. <strong>1.8 Limitation of the Study </strong> This research x-rays Government Expenditure on Education, school (primary, secondary and tertiary) enrolment as they relate to Growth of Nigeria Economy. Time series data covering the period 1981 to 2018 is used for this study. A study undertaken in 2020, but can not access 2019 data on the variables used, stand as one of the limitations, since lag periods are essential in policy implementation. Data availability, genuineness and accuracy of same, time and financial constraints, constitute limitations to this research work. Effect of corruption on government expenditure and outbreak of Corona virus, resulting to closure of tertiary institutions in Nigeria, also constitute limitation to this study. <strong>1.9 Organization of the Study </strong> This research work comprises of five (5) chapters, these includes; Chapter one: this consists of background to the study, Problem Statement, research questions, research hypothesis and scope of the study. Chapter two: consisting of conceptual framework, theoretical review, review of related literatures and theoretical framework. Chapter three: explained the methodology this research adopted. Chapter four: presentation of results and discussion of findings. Chapter five: consists of summary of findings, conclusion, policy recommendation, contribution to knowledge and suggestion for further studies.&nbsp; <strong>CHAPTER TWO</strong> <strong>LITERATURE REVIEW AND THEORITICAL FRAMEWORK</strong> <strong>2.1 Conceptual Review</strong> <strong>2.1.1 Government&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </strong> Government is the sector of the economy focusing on giving different public services. Its structure differs by nation, yet in many nations, government involves such services as infrastructure, military, police, public travel, government provided education, alongside medical services and those working for the public sector itself, like, elected authorities. The government may offer types of assistance that a non-taxpayer can&#39;t be barred from, (for example, street lighting), goods which aids all of society instead of benefiting only one person. Finances for government goods and services are generally obtained through various techniques, including taxes, charges, and through monetary transfers from different tiers of government (for example from federal to state government). Various governments from around the globe may utilize their own strategies for financing public goods and services. <strong>2.1.2 Government Expenditure</strong> Government Expenditure refers to government spending both capital and recurrent. For the purpose of this study we limited our scope to government educational expenditure in Nigeria. The theory of government expenditure is the theory of the costs of availing goods and services through planned spending (budget). There are two ways to deal with the subject of growth of government, precisely, the expansion in total size of government spending and the expansion of government in terms of economic magnitudes. Government expenditure is spending made by the public sector (government) of a nation on aggregate needs and wants, for example, pension and arrangement of infrastructure, among others. Until the nineteenth century, government speding was constrained, as free enterprise theorists believed that financial resources left in the private sector could lead to higher returns. In the twentieth century, John Maynard Keynes advocated the job of government spending in influencing levels of wages and income distribution in the economy. From that point forward government spending has demonstrated an expanding pattern. The public expenditure trend of the government of a nation is essentially the manner in which assets (resources) are distributed to the various segments of the economy where spending is required. It is exemplified in the government&rsquo;s ways of spending money. In analyzing the trend of government spending hence, it is critical to realize that under a federal system of administration, government job in dealing with the economy is the joint duty of the different tiers of government (Eze and Ikenna 2014). <strong>2.1.3 Human Capital </strong> By and large, human capital is characterized as all skills that are indistinguishably helpful to numerous organizations, including the training organization. Industry-specific skills, conversely, foster efficiency (productivity) just in the industry in which the skills were obtained. In a serious market setting, laborers consistently get a pay that approaches their minor profitability and in this manner, on account of general human capital, laborers win a similar compensation any place they work. <strong>2.1.4 Economic Growth</strong> As per Haller (2012), economic growth or economic expansion means the way toward expanding the size of a country&rsquo;s economy, its macro-economic indicators, particularly the per capita GDP, in an incremental yet not mandatorily linear course, with beneficial outcomes on the socio-economic sector. IMF (2012) perceives economic expansion as the expansion in the market worth of commodities created in a country over a period of time after discounting for inflation. The rate of increment in real Gross Domestic Product is often used as an estimate of economic expansion. In the perspectives of Kimberly (2012), economic expansion is an expansion in the creation of commodities. Any expansion in the worth of a nation&rsquo;s created commodities is likewise characterized as economic expansion. Economic expansion means an expansion in real GNP per unit of labor input. This relates to labor efficiency variation with time. Economic expansion is routinely estimated with the pace of increment in GDP. It is often estimated in real terms (deducting the impact of inflation on the cost of all commodities created). Growth improves the living standard of the individuals in that specific nation. As per Jhingan (2004), one of the greatest aims of money policy approach as of late has been quick macroeconomic expansion. He thus, characterized economic prosperity (growth) as the event whereby the real per capita earnings (income) of a nation increments over a significant stretch of time. Economic expansion is estimated by the expansion in the quantity of commodities created in a nation. An expanding economy creates more commodities in each subsequent timespan. In this manner, growth happens when an economy&#39;s capacity to produce increases which in turn, is utilized to create a greater quantity of commodities. In a more extensive perspective, economic expansion means increasing the living standard of individuals, and reducing disparities in earnings. &nbsp; <strong>2.1.5 </strong><strong>Gross Domestic Product</strong> - GDP Investopedia designates Gross Domestic Product (GDP) as the financial worth of marketable commodities created in a nation during any given duration of time. It is normally computed on a yearly or a quarterly premise. It comprises household and government consumption, government pay-outs, investments and net exports that exist in a sovereign territory. Set forth plainly, GDP is a broad estimation of a country&#39;s aggregate economic activity. &nbsp; <strong>2.1.6 Education</strong> There is no singular meaning of education and this is on the grounds that it indicates various things to various individuals, cultures and societies (Todaro and Stephen, 1982). Ukeje (2002), considers education to be a process, a product and a discipline. When viewed as a process, education is a group of activities which involves passing knowledge across age-groups (generations). When viewed as a product, education is estimated by the characteristics and attributes displayed by the educated individual. Here, the informed (educated) individual is customarily considered to be an informed and refined individual. While as a discipline, education is perceived in terms of the pros of well-structured knowledge which learners are acquainted with. Education is a discipline concerned with techniques of giving guidance and learning in institutions of learning in lieu of informal socialization avenues like rural development undertakings and education via parent-child interactions). It comprises both inherent (intrinsic) and instrumental worth. It is attractive for the person as well as for the general public. Education as private commodity directly aids the individuals who get it, which thusly influences the person&#39;s future pay (income) stream. At the macroeconomic level, a workforce that is superior in terms of education is thought to expand the supply of human capital in the economy and increment its efficiency (productivity). Considering the externalities pervasive in education, it is broadly acknowledged that the state has a key task to carry out in guaranteeing fair distribution of educational chances (opportunities) to the whole populace. This is especially critical in developing nations, for example, Nigeria that experiences the ill effects of elevated poverty levels, inequality and market imperfections. Enrolment might be viewed as the process of commencing participation in a school, which is the number of learners (students) adequately registered as well as participating in classes (Oxford dictionaries). 2.1.7 Primary Education Pupils usually commence learning at the elementary level when they are as old as 5 years or more. Pupils go through 18 terms equivalent to 6 years at the elementary level and may be awarded a first school leaving certification upon successful completion of learning. Subjects treated at the elementary stage comprise arithmetic, foreign and indigenous languages, culture, home economics, religious studies, and agric science. Privately owned institutions of learning may opt to treat computer science, and fine arts. It is mandatory to participate in a Common Entrance Examination in order to meet requirements for induction into secondary institutions of learning. <strong>2.1.8 Secondary Education In Nigeria</strong> Decades after the advancement of elementary education, government gave attention to secondary education, because of the requirement for pupils to advance their education in secondary schools. Secondary education is defined as the completion of fundamental education that started at the elementary level, and seeks to establish the frameworks for long-term learning and human development, by providing subject and skill-centred guidance. It is equally a link between elementary learning and tertiary learning. It is given in two phases, junior and senior levels of three years each and it is six-year duration. It was only in 1909 that the colonial administration began to supplement the endeavors of the Christian Missions in giving secondary education. This was when King&#39;s College was established in Lagos as the colonial government&#39;s secondary institution of learning. As per Adesina and Fafunwa , numerous laws were enacted to improve the condition of secondary education in Nigeria. For the duration of the time the nation was under Colonial Governments, there were scarcely any secondary schools to give secondary education to those that were then ready to gain it. 2.1.9 Tertiary Education Institutions of tertiary learning comprise universities, colleges of education, polytechnics and monotechnics. Government has dominant control of university education, and regulates them through National Universities Commission (NUC). At the university level, first year selection criteria include: At least 5 credits in not more than two sittings in WAEC/NECO; and a score above the 180 benchmark in the Joint Admission and Matriculation Board Entrance Examination (JAMB). Prospective entrants who hold satisfactory national certificates of education (NCE) or national diplomas (ND) having 5 or more ordinary level credits may gain direct entry into universities at the undergraduate level. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <strong>2.2 Theoretical Review</strong> <strong>2.2.1 Wagner&rsquo;s Law of Expending State Activity </strong> Public expenditure has one its oldest theories rooted in Adolph Wagner&rsquo;s (1883) work. A German economist that came up with a fascinating hypothesis of development in 1883 which held that as a country builds its public sector up, government spending will consequently become more significant. Wagner built up a &ldquo;law of increasing state activity&quot; after empirical investigation on Western Europe toward the conclusive part of the nineteenth century. Wagner&#39;s Law as treated to in Likita (1999) contended that government administration development is a product of advancement in industrialization and economic development. Wagner believed that during industrialization, the expansion of real earnings per capita will be accompanied by increments in the portion of government spending in total spending. He stated that the coming of industrial communities can bring about greater political impetus for social advancement and expanded earnings. Wagner (1893) stated three central reasons for the expansion in state spending. To start with, activities in the public sector will supplant non-private sector activities during industrialization. State duties like authoritative and defensive duties will increment. Furthermore, governments will be expected to give social services and government assistance like education, and public health for the elderly, subsidized food, natural hazards and disaster aids, protection programs for the environment and social services. Thirdly, industrial expansion will lead to novel&nbsp; technology and erode monopoly. Governments will need to balance these impacts by offering public goods through planned spending. Adolf Wagner in Finanzwissenschaft (1883) and Grundlegung der politischen Wissenschaft (1893) identified state spending as an &ldquo;internal&rdquo; factor, controlled by the development of aggregate earnings. Thus, aggregate earnings give rise to state spending. Wagner&#39;s may be viewed as a long-term phenomenon which is best observed with lengthy time-series for better economic interpretation and factual (statistical) derivations. This is because these patterns were expected to manifest after 5 or 10 decades of present day industrial community. The hypothesis of public spending is the hypothesis of the costs of availing commodities through planned government spending as well as the theory of policies and laws enacted to bring about private spending. Two ways to deal with the topic of the growth of the government sector are, namely, the expansion in volume of non-private spending and the expansion of non-private sector. Okafor and Eiya (2011) investigated the factors responsible for increment of government spending utilizing BLUE-OLS estimator. They discovered that population, government borrowing, government income, and inflation significantly affected government at the 5% level, while inflation most certainly did not. Further, Edame (2014) examined the predictive factors of state infrastructure spending in Nigeria, utilizing error correction modeling. In this study, it was found that growth-pace of urbanization, public income, density of population, system of government, and foreign reserves collectively or separately impact Nigeria&rsquo;s state infrastructure spending. &nbsp; <strong>2.2.3</strong><strong>The Classical Theory of Economic Growth</strong> This theory signifies the underlying structure of economic reasoning and Adam Smith&#39;s &quot;The Wealth of Nations&quot; (1776) typically paves the way for classical economics. Prominent and remarkable advocates of the classical school are: Adam Smith (1723-1790), David Ricardo (1772-1823), Thomas Malthus (1766-1834), Karl Marx (1818-1883), John Stuart Mill (1808-1873), Jean-Baptiste Say (1767-1832) and so on. Basically Smith&#39;s theory says that the endowment of countries was put together not with respect to gold, but with respect to commerce: As when two economic agents trade valuable commodities, in order to reap the benefits of trade, endowment grows. The classicalists see that markets are self-regulating, when liberated from compulsion. The classicalists termed this figuratively as the &quot;invisible hand&quot;, which establishes equilibrium, when consumers choose among various suppliers, and failure is allowed among firms that fail to compete successfully. The classicalists often warned against the risks of &ldquo;trust&rdquo;, and emphasized on free market economy (Smith, 1776). Adam Smith connected the expansion in endowment of individuals to the expansion of the yield of production factors, which manifests in the improvement of productivity of labor and an expansion in the quantity of working capital. Much scrutiny was given to population expansion, to the expansion in the portion of laborers in material production, to investment and geographical findings, which added to far-reaching prosperity. The perspectives of Thomas Malthus on economic expansion, portraying the expansion of populace and the expansion in production appeared pessimistic. As per Malthus, when the proportion between population expansion and subsistence methods&nbsp; remains, when the populace is expanding increasingly, and subsistence methods expand steadily, the aftermath will be inadequate earth resources (land), and consequently a severe battle for few resources, the prevalence of wars, plagues, hunger, mass illness, etc (Ojewumi and Oladimeji, 2016). As a solution to this issue, Malthus proposed to limit the growth of the populace by the &quot;call to prudence&quot;, particularly the impoverished, and the birth of children on the bases that they were to be provided with decent means of subsistence. One among the most compelling classicalists was David Ricardo (1772 &ndash; 1823). Apparently, the hypothesis of comparative advantage which recommends that a country should engage exclusively in internationally competitive businesses and trade with different nations to acquire commodities lacking domestically is his most notable contribution. He contended the possibility of the presence of a natural market wages and expected that new technologies will result to a fall in the demand for labor. John Stuart Mill (1808-1873) to a great extent summarized the past ideologies of the classicalists. Specifically, he finished the classicalists&rsquo; hypothesis of economic dynamics that considers long-term economic patterns. At the core of this idea is the unceasing amassing of capital. As indicated by the hypothesis, the expansion in capital prompts an increment in the need for labor, and zero population growth gives rise to increment in real earnings, and therefore gives rise to population expansion in the long-run. When the amassing of capital is quicker than the expansion in the workforce, both of these processes can, in principle, remain forever. Increment in the quantity of laborers means having more &quot;mouths&quot;, hence the expansion in the demand for consumption and particularly for food. Food created in agribusiness, which, as we know, characterized by diminishing returns to scale. Therefore, issues of diminishing marginal productivity of capital emerge and the fall of incentives to invest. <strong>2.2.4 The Keynesian Approach of Public Expenditure </strong> John M. Keynes (1936), a British Economist and the pioneer of macroeconomics contended that public spending is a crucial determinant of economic posperity. Keynes hypothesis clearly stated that fiscal policy instrument (for example government expenditure) is a significant apparatus for obtaining stability and better economic expansion rate in the long-term. To obtain stability in the economy, this hypothesis endorses government action in the economy through macroeconomic policy especially fiscal policy. From the Keynesian view, government spending will contribute incrementally to economic expansion. Keynes contended that it is necessary for government to mediate in the economy since government could change financial downturns by raising finances from private borrowing and afterward restoring the funds to the private sector through several spending programs. Likewise, government capital and recurrent spending in the structure provision of class rooms, research centers, acquisition of teaching and learning aids including PCs and payment of salary will have multiplier effects on the economy. Spending on education will boost productivity as well as advancement by improving the quality of labour. It will likewise help in developing a stream of educated administrators in both the private and public sectors of the economy. Keynes classified public spending as an exogenous variable that can create economic prosperity rather than an endogenous phenomenon. In summary, Keynes acknowledged the functioning of the government to be significant as it can prevent economic downturn by expanding aggregate demand and in this manner, switching on the economy again by the multiplier effect. It is an apparatus that proffers stability the short-term yet this should be done carefully as excessive government spending leads to inflation while lack of spending aggravates unemployment. &nbsp; <strong>2.2.5 </strong><strong>Human Capital Theory</strong> Human capital theory, at first developed by Becker (1962), contends that workers have a set of abilities which they can improve or acquire by learning and instruction (education). Be that as it may, human capital hypothesis often assume for the most part expect that experiences are converted into knowledge and skills. It helps us comprehend the training activities of organizations. It (re-)introduced the view that education and training add up to investment in future efficiency (productivity) and not only consumption of resources. From this viewpoint, both firms and labourers rely upon investment in human capital to foster competitiveness, profitability, and earnings. In spite of the fact that these advantages are self-evident, these investments are tied to some costs. From the firm&#39;s perspective, investment in human capital contrast from those in physical capital, because the firm doesn&#39;t gain a property right over its investment in skills, so it and its employees need to agree on the sharing of costs and benefits derived from these investments. While investment in physical capital are solely the organization&#39;s own choice, investment in the abilities (skills) of its workforce include interaction with the workers to be groomed. In the basic formulation, Becker, assuming that commodity and labour markets are perfectly competitive, introduced the distinction between firm-specific and general human capital to answer the question: who bears the expenses of training? &nbsp; <strong>2.2.6 Neoclassical Growth Theories </strong> The neoclassical development hypotheses arose in the 1950s and 1960s, when regard for the issues of dynamic equilibrium declined and the issue of actualizing growth potentials through the adoption of novel technology, boosting productivity and improving the organization of production gained popularity. The principle advocates of this school are Alfred Marshall (1842-1924), Leon Walras (1834-1910), William Stanley Jevons (1835-1882), Irving Fisher (1867-1947) and others. The American economist Robert Solow (1924-present) along with other economists opposed the state&#39;s participation and rather supported the notion of permitting firms to competitively grow by utilizing the majority of the assets accessible to them. They hinged on the production theory and marginal productivity theory from the classical school, according to which, the earnings obtained production factors depend on their marginal products. Neoclassical scholars disagreed with neo-Keynesian views on growth on three grounds (UN, 2011): Firstly, in light of the fact that they are centered around capital accumulation, overlooking land, labour, technology and so on; On the second note, owing to the fact that they are rooted in the unchanging nature of capital share in earnings (income); On the third note, while the neoclassicists recognized the self-restoring equilibrium of the market mechanism, the former overlooked it. On this premise, they identified inflationary government spending as a source of instability in the economy. <strong>2.2.7 The Endogenous Growth Theory</strong> This was created as a response to exclusions and inadequacies in the Solow-Swan model. This theory throws light on long-term economic expansion pace based on the pace of population expansion and the pace of technical advancement which is autonomous with regards to savings rate. Since long-term economic expansion rate depended on exogenous factors, Romer (1994) saw that the neoclassical hypothesis had hardly limited implications. As per Romer, in models with exogenous technical change and exogenous population expansion, it never truly made a difference what the public administration did. The new growth theory doesn&#39;t rebuff the neoclassical growth theory. Perhaps it broadens the neoclassical growth hypothesis by incorporating endogenous technical advancement in growth models. The endogenous development models have been improved by Kenneth J. Arrow, Paul M. Romer, and Robert E. Lucas. The endogenous development model highlights technical advancement arising from pace investment, quantity of capital, and human capital supply. Romer saw natural assets as a lower priority than ideas. He refers to case of Japan which has limited natural assets but welcomed novel ideas and technology from the West. These included improved plans for production of producer durable goods for final production. Accordingly, ideas are key in economic prosperity. With respect to endogenous growth theory, Chude and Chude (2013) submitted that the major improvement in the endogenous growth hypothesis in relation to the past models lies in the fact that it treats the determinants of technology. That is, it openly attempts to model technology instead of expecting it to be exogenous. Momentously, it is a statistical clarification of technological improvement that introduced a novel idea of human capital, knowledge and abilities (skills) that empower employees to be increasingly productive. More often than not, economic expansion is a product of progress in technology, arising from effective utilization of productive resources through the process of learning. This is because human capital development has high rate or increasing rate of return. Therefore, the rate of growth depends heavily on what (the type of capital) a country invests in. Thus to achieve economic expansion, public expenditure in human capital development especially education spending must be increased. At the same time, the theory predicts unexpected additional benefits from advancement of a substantial valued-added knowledge economy, that can develop and preserve a competitive advantage in expanding industries. <strong>2.3 Empirical Review</strong> Bearing in mind the sensitive nature of the field being studied, many investigations had been conducted with the aim of clarifying the divergent ideological schools. For example, Amadi, and Alolote, (2020) explored government infrastructural spending and Nigeria&rsquo;s economic advancement nexus. The investigation uncovered that public spending on transport, communication, education and medical infrastructure significantly affect economic expansion, while spending on agric and natural resources infrastructure recorded a major adverse impact on economic expansion. Despite the fact that the investigation is recent, the time series variables were not exposed to unit root tests with breaks, and thus will yield misleading outcomes. Shafuda and Utpal (2020) explored government spending on human capital and Namibia&rsquo;s economic prosperity (growth) nexus from 1980 to 2015. The examination utilized human development indicators like healthcare outcomes, educational accomplishments and increment in national earnings in Namibia. The investigation uncovered huge effects of government spending on medical care and education on GDP expansion over the long-term. Study conducted in 2020 that utilized data from 1980-1915, comprises a setback to this work. Ihugba, Ukwunna, and Obiukwu (2019) explored government education spending and Nigeria&rsquo;s elementary school enrolment nexus by applying the bounds testing (ARDL) method of cointegration during the time of 1970 to 2017. The model utilized for the investigation attempted to recognize the interaction between two variables and their relationship with control variables; per capita earning (income), remittances, investment and population expansion. The bounds tests indicated that the variables that were studied are bound together over the long-term, when elementary school enrolment is the endogenous variable. The investigation saw that an inconsequential relationship exists between government education spending on elementary school enrolment while a positive relationship exists among remittances and primary school enrolment. Sylvie (2018) explored education and India&rsquo;s economic expansion nexus. The investigation inspected the connection among education and economic prosperity in India from 1975 to 2016 by concentrating on elementary, secondary and tertiary levels of education. It used econometric estimations with the Granger Causality Method and the Cointegration Method. The study indicated that there is convincing proof demonstrating a positive association between education levels and economic expansion in India which may impact government activities and shape the future of India. Ayeni, and Osagie (2018), explored education spending and Nigeria&rsquo;s economic expansion nexus from 1987 to 2016. The investigation uncovered that education spending was inconsistent with education sectoral yield (output), while recurrent education spending had meaningful relationship with real gross national output (or GNP), conversely, capital spending on education was weak. Ogunleye, Owolabi, Sanyaolu, and Lawal, (2017), utilized BLUE-OLS estimator to study the effect of advancement in human capital on Nigeria&rsquo;s economic expansion from 1981 to 2015. The empirical outcomes indicated that human capital development has strong effects on economic expansion (growth). Likewise, human capital development variables; secondary school enrolment, tertiary enrolment, aggregated government spending on health and aggregated government spending on education displayed positive and strong effect on economic expansion of Nigeria. Glylych, Modupe and Semiha (2016) explored education and Nigeria&rsquo;s economic expansion nexus utilizing BLUE-OLS estimator to unveil the interaction between education as human capital and real Gross Domestic Product. The investigation found a strong connection between GDP and different indicators (capital spending on education, recurrent spending on education, elementary school enrolment and secondary school enrolment) utilized in the investigation except for elementary school enrolment (PRYE). Lingaraj, Pradeep and Kalandi (2016) explored education expenditure and economic expansion nexus in 14 major Asian nations by utilizing balanced panel data from 1973 to 2012. The co-integration result indicated the presence of long-run relationships between education spending and economic expansion in all the nations. The findings additionally uncovered a positive and significant effect of education training on economic advancement of all the 14 Asian nations. Further, the panel vector error correction showed unidirectional Granger causality running from economic expansion to education spending both in the short and long-run, however, education spending only Granger causes long-run economic expansion in all the nations. The findings likewise demonstrated a positive effect of education spending on economic expansion. The study contended that education sector is one of the significant elements of economic expansion in each of the 14 Asian nations. A significant portion of government spending ought to be made on education by upgrading different essential, senior and technical educations in the respective countries to make available the skilled labour for long-term economic advancement. Ojewumi and Oladimeji (2016) explored government financing and Nigeria&rsquo;s education nexus. In the research work, public spending on education was arranged into two classes (recurrent and capital spending). The data covered the period 1981 to 2013 and were secondary in nature. The data were gotten for the most part from the publications of the World Bank, Central Bank of Nigeria and National Bureau of Statistics. BLUE-OLS estimator was utilized to study the data. The main results indicated that the effect of both capital and recurrent spending on education expansion were negative during the examination time frame. The study suggested that the elevated level of corruption common in the educational sector ought to be checked to guarantee that finances ear-marked for education particularly capital spending in the sector are prudently appropriated. Government at various levels ought to likewise increment both capital and recurrent spending to support the educational sector up to the United Nations standard. Obi, Ekesiobi, Dimnwobi, and Mgbemena, (2016) explored government education spending and Nigeria&rsquo;s education outcome nexus from 1970 &ndash; 2013. The investigation utilized BLUE-OLS estimator, and demonstrated that government spending on education has a cordial and notable impact on education. Public health spending and urban population expansion were likewise found to positively affect education outcome but are insignificant in influencing education outcome. Omodero, and Azubike, (2016), explored government spending on education and Nigeria&rsquo;s economic advancement nexus from 2000&ndash;2015. Multiple regression analysis and student t-test were applied for investigation. The outcome of the investigation showed that education spending is significant and affects the economy. Additionally, education enrolment demonstrated a significant relationship with GDP but minor effect on the economy. Muhammad and Benedict (2015) explored education spending and Nigeria&rsquo;s economic expansion nexus during the time covering 1981-2010. Co-joining and Granger causality tests were utilized so as to unveil the causal nexus between education spending and economic expansion. They found that there is co-integration between real growth rate of GDP, aggregated government spending on education, recurrent expenditure on education and elementary school enrolment. Adeyemi and Ogunsola (2016) explored advancement in human capital and Nigeria&rsquo;s economic expansion nexus from 1980-2013 on secondary school enrolment, life expectancy rate, government spending on education, gross capital formation and economic expansion rate. ARDL cointegration approach was utilized in the investigation and it uncovered a positive since a long-run nexus among secondary school enrolment, life expectancy rate, government spending on education, gross capital formation and economic expansion rate. Olalekan (2014) explored human capital and Nigeria&rsquo;s economic expansion nexus utilizing yearly data on education and health, from 1980 to 2011. The investigation made use of Generalized Method of Moment (GMM) techniques in the research and the estimated outcomes gave proof of positive connection between human capital and economic expansion. Oladeji (2015) explored human capital (through education and effective services in healthcare) and Nigeria&rsquo;s economic expansion nexus from 1980 to 2012. The investigation utilized BLUE-OLS estimator and uncovered that there is a significant functional and institutional connection between the investment in human capital and economic expansion. The work indicated that a long-term nexus existed between education and economic expansion rate. Hadir and Lahrech, (2015) explored human capital advancement and Morocco&rsquo;s economic expansion nexus utilizing yearly data from 1973 to 2011. The BLUE-OLS estimator was incorporated utilizing aggregated government spending on education and health, the enrolment data of tertiary, secondary and elementary educational institutions as a measure for human capital. The research uncovered a positive nexus between aggregated government spending on education, aggregated government spending on health, elementary education enrolment, secondary education enrolment and tertiary education enrolment. Obi and Obi (2014) explored education spending and Nigeria&rsquo;s economic expansion nexus as a method for accomplishing ideal socio-economic change required from 1981 to 2012. The Johansen co-integration method and BLUE-OLS estimator econometric methods were utilized to closely study the connection between GDP and recurrent education spending. The results showed that regardless of the fact that a positive relationship was obtainable between education spending and economic expansion, a long-term nexus was not obtainable over the period under examination. Jaiyeoba (2015) explored investment in education/health and Nigeria&rsquo;s economic expansion nexus from 1982 to 2011. He utilized trend analysis, the Johansen cointegration and BLUE-OLS estimator. The outcomes demonstrated that there was long-term connection between government spending on education, health and economic expansion. The factors: health and education spending, secondary and tertiary enrolment rate and gross fixed capital formation carried the speculated positive signs and were notable determinants (apart from government spending on education and elementary education enrolment rate). Sulaiman, Bala, Tijani, Waziri and Maji (2015) explored human capital /technology and Nigeria&rsquo;s economic expansion nexus. They utilized yearly time series covering 35 years (1975-2010) and applied autoregressive distributed lag method of cointegration to look at the connection between human capital, technology, and economic expansion. Two measures of human capital (secondary and university enrolment) were utilized in two different models. Their outcome uncovered that all the factors in the two separate models were cointegrated. Besides, the findings from the two assessed models indicated that human capital in measured by secondary and tertiary education enrolments have significant positive effect on economic expansion. Borojo and Jiang (2015) explored education/health (human capital) and Ethiopia&rsquo;s economic expansion nexus from 1980 to 2013. Human capital stock is measured by elementary, secondary and tertiary education enrolment. Human capital investment is proxied by spending on health and education. The Augmented Dickey Fuller test and Johansen&#39;s Co-integration method were utilized to test unit root and to ascertain co-integration among factors, respectively. Their investigation indicated that public spending on health as well as education and elementary as well as secondary education enrolments has positive and significant impacts on economic expansion both in the short-term and the long-term. Ekesiobi, Dimnwobi, Ifebi and Ibekilo (2016) explored public education investment and Nigeria&rsquo;s manufacturing yield nexus. The investigation utilized Augmented Dickey Fuller (ADF) unit root test and BLUE-OLS estimator to examine the connection between public educational spending, elementary school enrolment rate, per capita income, exchange rate, FDI and manufacturing yield (output) rate. The investigation discovered that public education spending has a positive but inconsequential impact on manufacturing yield (output) rate. Odo, Nwachukwu, and Agbi (2016) explored government spending and Nigeria&rsquo;s economic expansion nexus. Their finding demonstrated that social capital had inconsequential positive effect on economic expansion during the period under consideration. Jiangyi, (2016) explored government educational spending and China&rsquo;s economic expansion nexus bearing in mind the spatial third-party spill-over effects. The findings uncover that public educational spending in China has a significant positive effect on economic expansion, but spending in various educational level shows varying outcomes. Public educational spending beneath high-education is positively related with domestic economic expansion, while the impact of educational spending in high-education is inconsequential. Lawanson (2015) explored the importance of health and educational elements of human capital to economic expansion, utilizing panel data from sixteen West African nations over the period 1980 to 2013. He utilized Diff-GMM dynamic panel procedure. The empirical results show that coefficients of both health and education have positive and significant impacts on GDP per capita. The paper ascertains the importance of human capital to economic expansion in West Africa. He suggested that more assets and policies to persuade and improve access to both education and health by the populace ought to be sought after by policy makers. Ehimare, Ogaga-Oghene, Obarisiagbon and Okorie (2014), explored the connection between Nigerian government Expenditure and Human Capital Development. The level of human capital development, which is a measure of the degree of wellbeing (health) and educational achievement of a country influence the level of economic activities in that country. The unit root test was employed to ascertain if the stationary or non-stationary with the Phillip Peron test. So as to measure the efficiency of government spending on human capital development, the data analysis was performed with Data Envelopment Analysis including Input Oriented Variable Return to Scale. The discoveries of the study uncovered that there has been substantial decrease in the efficiency of government spending since 1990 up till 2011 which has been diminishing. Ajadi and Adebakin (2014), investigated the nature of association between human capital development and economic expansion. The descriptive survey method of research was incorporated and multi&ndash;stage sampling method was utilized to choose a size of 200 respondents utilized for the research. An adopted questionnaire with 0.86 reliability index was utilized for information gathering. Data gathered were examined utilizing the Pearson&#39;s Product Moment Correlation Coefficient. The results demonstrated that education has a predictive r-value of 0.76 on individual personal earnings and the type of occupation (job) is linked with individual personal earnings (r=0.64). It, subsequently, concluded that economic expansion rate is influenced by individual personal earnings and suggested that government ought to create adequate educational policy to avail the human capital need of the populace for economic prosperity. Harpaljit, Baharom and Muzafar (2014) examined the connection between education spending and economic expansion rate in China and India by utilizing yearly data from 1970 to 2005. This investigation used multi econometric methods including co-integration test, BLUE-OLS estimator, and VECM. The result uncovered that there is a long-term nexus between earnings (income) level, Gross Domestic Product per capital and education spending in both China and India. Also, a unidirectional causal relationship was obtained for the two nations, running from earnings (income) level to education spending for China, while for India, education spending Granger causes the level of earnings. Urhie (2014) analyzed the impacts of the components of public education spending on both educational achievement and Nigeria&rsquo;s economic expansion rate from 1970 to 2010. The investigation utilized Two Stage Least Squares estimation procedure to analyze the hypotheses. The result uncovered that both capital and recurrent spending on education affect education achievement and economic expansion rate differently. Recurrent spending negatively affected education while capital spending was found to have a positive effect. Conversely, recurrent education had a positive and notable effect on economic expansion while capital spending had a negative effect. Chude and Chude (2013) explored the impacts of public education spending on Nigeria&rsquo;s economic expansion over a time frame from 1977 to 2012, with particular focus on disaggregated and sectorial spending analysis. Error correction model (ECM) was utilized. The result uncovered that over the long-term, aggregated education spending is significant and has a positive relationship on economic expansion. Abdul (2013), analyzed Education and Economic expansion in Malaysia given the fact human capital or education has is now one of the focal issues in the research of economic advancement. The researcher contended that the current studies showed that human capital, particularly education, is a significant ingredient of economic expansion. Thus the researcher investigated the issue of Malaysia education data. Notwithstanding a few issues and data quality issues, Malaysian education datasets are heavily correlated for both secondary and tertiary education. The researcher further tests the impact of various datasets on education and economic expansion relationship. The results were fundamentally the same thereby indicating that Malaysian education datasets are not unreliable. The results were econometrically consistent irrespective of measure of education utilized. All datasets lead to the same conclusion; education is inversely associated with economic expansion. Alvina and Muhammad (2013), inspected the long-term connection between government education spending and economic expansion. The investigation utilized heterogeneous panel data analysis. Panel unit root test are applied for checking stationarity. The single equation approach of panel co-integration (Kao, 1999); Pedroni&#39;s Residual-Based Panel of co-integration Test (1997, 1999) was applied to ascertain the presence of long-term connection between public education spending and gross domestic production. Finally Panel fully modified OLS result uncovered that the effect of government public education on economic expansion is more prominent in developing nations as contrasted with the developed nations, which confirmed the &quot;catching-up effect&quot; in developing nations. Mehmet and Sevgi (2013), inspected the nexus between education spending and economic expansion in Turkey. The examination utilized econometric method as the principal investigation instrument. The result uncovered a positive connection between education spending and economic expansion in the Turkish economy for the period 1970-2012. Implying that, education spending in Turkey positively affected economic expansion. Edame (2014) researched the determinants of Nigeria&rsquo;s public infrastructure spending, utilizing ECM. He found that pace (rate) of urbanization, government income, population density, external reserves, and kind of government collectively or independently impact on public spending on infrastructure. Aregbeyen and Akpan (2013) examined the long-term determinants of Nigeria&rsquo;s government spending, utilizing a disaggregated approach. In their examination, they found that foreign aid is significantly and positively influencing recurrent spending to the detriment of capital spending; that income (revenue) is likewise positively influencing government spending; that trade transparency (openness) is adversely impacting government spending; that debt service obligation diminishes all parts of government spending over the long-term; that the higher the size of the urban population, the higher would be government recurrent spending on economic services; solid proof that Federal government spending is one-sided with regards to recurrent spending, which increments substantially during election times. In likewise manner, Adebayo et al. (2014) researched the effect of public spending on industrial expansion of Nigeria through co-integration and causality and discovered that public spending on administration, economic services, and transfers remained negatively related with industrial expansion while government spending on social services remained positively related in the long-term. They concluded in this manner that there is no crowding-out impact. From these studies reviewed, there is proof that all the investigations joined economic, social, and political determinants of government spending. Srinivasan (2013), analyzed the causal nexus between public spending and economic expansion in India utilizing co-integration approach and error correction model from 1973 to 2012. The co-integration test result uncovered the presence of a long-term equilibrium connection between public spending and economic expansion. The error correction model estimate indicated unilateral causality which runs from economic expansion to public spending in the short-term and long-term. Mohd and Fidlizan (2012), narrowed down on the long-term relationship and causality between government spending in education and economic expansion in Malaysian economy from 1970-2010. The investigation utilized Vector Auto Regression (VAR). The result indicated that economic expansion co-integrated with fixed capital formation (CAP), labour force participation (LAB) and government spending on education (EDU). The Granger cause for education variable and vice versa. In addition, the investigation demonstrated that human capital like education variable goes a long way in affecting economic expansion. Consensus from the above investigations demonstrates that government spending impacts positively on economic expansion. Notable theories that support this case include; Keynes, Wagner, Peacock and Wiseman. Keynes, in his hypothesis draws a connection between public spending and economic expansion and infers that causality runs from public spending to income, meaning that public sector spending is an exogenous factor and public instrument for expanding national income. Again, it holds that expansion in government spending prompts higher economic expansion. Wagner, Peacock and Wiseman and numerous economists have developed various theories on public spending and economic expansion. Wagner positioned public sector spending as a behavioral variable that positively indicates if an economy is prospering. Notwithstanding, the neo classical growth model created by Solow opined that the fiscal policy doesn&#39;t have any impact on the expansion of national income. These multifaceted results obtained from prior investigations show that in reality public spending and other inputs in the education system may have some innate heterogeneity, suggesting that what holds in a given area or country may not hold in another. In the light of the above, this investigation sees that it is necessary to revise the allotment of public spending on education, with regards to the type of impact this spending has on education outcomes. <strong>2.4 Theoretical Framework</strong> The endogenous growth theory has been adopted as the appropriate theoretical framework for this study. This owes much to the fact that, the theory emphasizes the critical role of human capital development, through public investments on education, as a major driver of aggregate productivity in the economy. This is also supported by the work of Ogunleye, Owolabi, Sanyaolu, and Lawal, (2017) who ascertained how economic expansion is influenced by advancement in human capital from 1981 to 2015. In this study it was discovered that economic expansion is greatly influenced by advancement in human capital. Also, economic expansion appeared to facilitated by secondary education enrolment, tertiary education enrolment, and aggregate spending on health and education by the government. <strong>2.5 Research Gap</strong> Though, so much research work has been carried out on the relationship between human capital development, Public Sector Expenditure on Education and Economic expansion in Nigeria, a lot still needed to be done to address some abnormities in these studies. Of note, is that methods adopted in most of these studies are faced with methodological limitations and policy carry-overs, not minding that no two economies are the same. This study therefore, seeks to fill these gaps created by previous researches. Importantly, time plays a vital role in research, making it imperative for continuous and up to date studies, so as to keep abreast with changes as quickly as possible. In the study carried out by Ojewumi and Oladimeji (2016), time series data covering from 1981-2013 was used, while Muhammad and Benedict (2015), used time series data from 1981-2010. These studies above used time series data of 1981 to 2013 and 1981 to 2010 respectively, while this study used updated data covering 1981-2018, thereby making the study current and up to date. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <strong>Chapter Three</strong> <strong>Research Methods</strong> <strong>3.1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Research Design</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ex post facto research design and econometric procedures of analysis will be employed for empirical investigation. <strong>3.2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Model Specification</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Here, we specify a model which captures the relationship between real gross domestic product in per capita terms and the selected education enrolment variables. &nbsp; &nbsp; (3.1) In the above model, <em>Ln</em> denotes natural log, <em>PER_RGDP</em> denotes real gross domestic product in per capita terms,<em> PER_PEE</em> denotes public expenditure on education in per capita terms, <em>PENR</em> denotes percentage of primary education enrolment from population total, <em>SENR</em> denotes percentage of secondary education enrolment from population total, and <em>TENR</em> denotes percentage of tertiary education enrolment from population total. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; For further empirical analysis we can explicitly express the above model in the form of an autoregressive distributed lag (ARDL) model: &nbsp; &nbsp; (3.2) Here, based on economic theory and intuition all of the coefficients are expected to be positive. <strong>3.3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Estimation Procedure</strong> <strong>3.3.1&nbsp;&nbsp;&nbsp; Unit Root Test with Breaks</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Unlike the popularly used unit root tests (e.g. ADF and PP) which test the null of non-stationarity without accounting for possible breaks-points in data, the break-point unit root test of Peron (1989) tests the null of non-stationarity against other alternatives while accounting for a single break-point in the given data. The alternative hypotheses for this test are succinctly described in the following equations: &nbsp; &nbsp; (3.3) &nbsp; &nbsp; (3.4) &nbsp; &nbsp; (3.5) The first equation captures a break in the intercept of the data with the intercept-break dichotomous variable <em>I_t</em> which takes on values of 1 only when <em>t</em> surpasses the break-point <em>Br</em>; the second captures a break in the slope of the data with a regime-shift dichotomous variable <em>T_t*</em> which takes on values of 1 only when <em>t </em>surpasses the break-point <em>Br</em>; and the third equation captures both effects concurrently with the &ldquo;crash&rdquo; dichotomous variable <em>D</em> which takes on values of 1 only when <em>t</em> equals <em>Br</em>+1. <strong>3.3.2&nbsp;&nbsp;&nbsp; ARDL Bounds Cointegration Approach</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The popularly-used residual-based cointegration methods may not be very useful when the time-series under consideration attain stationarity at different levels. On the other hand, in addition to being econometrically efficient for small sample cases (<em>n</em> &lt; 30), the bounds cointegration method developed by Pesaran and Shin (1999) is particularly useful for combining time-series that attain stationarity at levels and first-difference. The bounds cointegration method makes use of upper bounds and lower bounds derived from 4 pairs of critical values corresponding to 4 different levels of statistical significance: the 1% level, the 2.5% level, the 5% level, and the 10% level. The null of &ldquo;no cointegration&rdquo; is to be rejected only if the computed bounds f-statistic surpasses any of the upper bounds obtained from a chosen pair of critical values, while the alternative hypothesis of cointegration is to be rejected only if the bounds f-statistic falls below any of the lower bounds obtained from a chosen pair of critical values. Therefore, in contrast to other cointegration tests, the bounds test can be inconclusive if the bounds f-statistic neither surpasses the chosen upper bound nor falls below the chosen lower bound. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; To obtain the bounds f-test statistic, an f-test is performed jointly on all of the un-differenced explanatory variables of the &ldquo;unrestricted&rdquo; error correction model (ECM) derived from any corresponding autoregressive distributed lag (ARDL) model such as the previously specified empirical ARDL model in (3.2). This takes the general form: &nbsp; &nbsp; (3.6) where &Delta;<em>i_t</em> denotes the chosen endogenous variable in first difference; &Delta;<em>j_t</em> and &Delta;<em>k_t</em> denote the chosen exogenous variables in first differences;&nbsp; and <em>e_t</em> denotes the stochastic component. Choosing the best lag-length to be included is made possible by information criteria such as the Akaike and the Schwarz Information Criterion. In the case where the bounds cointegration test disapproves the null, a &ldquo;restricted&rdquo; version of the error correction model can be estimated along-side a long-run model to capture the relevant short-run and long-run dynamics as seen in the following expressions: &nbsp; &nbsp; (3.7) &nbsp; &nbsp; (3.8) Here, the error correction term <em>_t</em>_-1 is non-positive and bounded between 0 and 1 (or 0 and 100) in order to capture the short-run rate of adjustment to long run equilibrium, while the coefficients <em>₁</em>,&hellip;,<em>_j</em>&nbsp; in (3.7) capture the state of long-run equilibrium and are obtained from <em>₁</em>=<em>b₂</em>/<em>b₁</em>,&hellip;, <em>_j</em>=<em>b_j</em>/<em>b₁</em> respectively. &nbsp; &nbsp; &nbsp; <strong>3.4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Model Evaluation Tests and Techniques</strong> <strong>3.4.1&nbsp;&nbsp;&nbsp; R² and Adjusted R²</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The R² and the adjusted R² both provide measures of goodness-of-fit. However, the adjusted R² is preferably used because it is robust against redundant regressors which inflate the conventional R². They involve the following statistics: &nbsp; &nbsp; (3.9) &nbsp; &nbsp; (3.10) where <em>SS_r</em> denotes the sum of squares of the regression residuals, <em>SS_t</em> denotes the total sum of squares of the dependent variable, <em>n</em> denotes the number of observations, and <em>k</em> denotes the number of regressors (Verbeek, 2004). <strong>3.4.2&nbsp;&nbsp;&nbsp; T-Test and F-Test</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The t-test and the f-test can be utilized to evaluate hypotheses pertaining to statistical significance of the parameters in a regression. Particularly, the t-test may be applied to a single parameter while the f-test may be applied to multiple parameters. They involve the following statistics: &nbsp; &nbsp; (3.11) &nbsp; &nbsp; (3.12) where <em>a_k</em> denotes a single parameter-estimate, <em>se </em>denotes its standard error, <em>R²</em> denotes the coefficient of determination of the regression, <em>N</em> denotes the number of observations, and <em>J</em> denotes the number of regressors. For the t-test, the statistical insignificance null hypothesis is to be rejected only if <em>t_i</em> exceeds its 5% critical-value, while for the f-test the joint statistical insignificance null hypothesis is to be rejected only if <em>f</em> exceeds its 5% critical-value at <em>N-J</em> and <em>J-1</em> degrees of freedom (Verbeek, 2004). <strong>3.4.3&nbsp;&nbsp;&nbsp; Residual Normality Test</strong> The Jarque-Bera test statistic (Jarque and Bera, 1987) is useful in determining whether the residuals of a regression are normally distributed. The Jarque-Bera statistic is computed as: &nbsp; &nbsp; (3.13) where <em>S</em> is the skewness, <em>K</em> is the kurtosis, and <em>N</em> is the number of observations. Under the null hypothesis of a normal distribution, the Jarque-Bera statistic is distributed as <em>X²</em> with 2 degrees of freedom. Therefore, the null hypothesis is to be accepted if the absolute value of the Jarque-Bera statistic exceeds the observed value under the null hypothesis. Contrarily, the null hypothesis is to be rejected if the absolute value does not exceed the observed value. <strong>Heteroskedasticity Test</strong> The Breusch-Pagan-Godfrey test (Breusch and Pagan, 1979; Godfrey, 1978) evaluates the null hypothesis of &ldquo;no heteroskedasticity&rdquo; against the alternative hypothesis of heteroskedasticity of the form , where is a vector of independent variables. The test is performed by completing an auxiliary regression of the squared residuals from the original equation on . The explained sum of squares from this auxiliary regression is then divided by to give an LM statistic, which follows a chi square <em>X² </em>distribution with degrees of freedom equal to the number of variables in <em>Z </em>under the null hypothesis of no heteroskedasticity. Therefore, the null hypothesis is to be accepted if the LM statistic exceeds the observed value under the null hypothesis. Contrarily, the null hypothesis is to be rejected if the LM statistic does not exceed the observed value. <strong>3.4.5&nbsp;&nbsp;&nbsp; Serial Correlation Test</strong> The Godfrey (1978) Lagrange multiplier (LM) test is useful when testing for serial correlation in the residuals of a regression. The LM test statistic is computed as follows: First, assuming there is a regression equation: &nbsp; &nbsp; (3.14) where <em>&beta;</em> are the estimated coefficients and <em>&epsilon;</em> are the errors. The test statistic for the lag order <em>&rho;</em> is based on the regression for the residuals <em>&epsilon; = y - XḂ</em> which is given by: &nbsp; &nbsp; (3.15) The coefficients <em>𝛾</em> and <em>𝛼</em><em>_&delta;</em>are expected to be statistically insignificant if the null hypothesis of &ldquo;no serial correlation&rdquo; is to be accepted. On the other hand, the null hypothesis cannot be accepted if the coefficients <em>𝛾</em> and <em>𝛼</em><em>_&delta;</em>are found to be statistically significant. <strong>3.4.6&nbsp;&nbsp;&nbsp; Model Specification Test</strong> The Ramsey (1969) Regression Error Specification Test (RESET) is a general test for the following types of functional specification errors: Omitted variables; some relevant explanatory variables are not included. Incorrect functional form; some of the dependent and independent variables should be transformed to logs, powers, etc. Correlation between the independent variables and the residuals. Ramsey (1969) showed that these specification errors produce a non-zero mean vector for the residuals. Therefore, the null and alternative hypotheses of the RESET test are: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; (3.16) The RESET test is based on an augmented regression which is given as: &nbsp; &nbsp; (3.17) The test of the null hypothesis of a well-specified model is tested against the alternative hypothesis of a poorly specified model by evaluating the restriction <em>𝛾</em><em> = 0</em>. The null hypothesis is to be accepted if <em>𝛾</em><em> = 0</em>, whereas the null hypothesis is to be rejected if <em>𝛾</em><em> &ne; 0</em>. The crucial factor to be considered in constructing the augmented regression model is determining which variable should constitute the <em>Z</em> variable. If <em>Z</em> is an omitted variable, then the test of <em>𝛾</em><em> = 0</em> is simply the omitted variables test. But if <em>y</em> is wrongly specified as an additive relation instead of a multiplicative relation such as <em>y =</em><em>𝛽</em><em>₀</em> X^𝛽¹X^𝛽² + 𝜖 then the test of <em>𝛾</em><em> = 0 </em>is a functional form specification test. In the latter case the restriction <em>𝛾</em><em> = 0 </em>is tested by including powers of the predicted values of the dependent variables in <em>Z</em> such that . <strong>3.4.7&nbsp;&nbsp;&nbsp; CUSUMSQ Stability Test</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; For the test of stability, cumulative sum of recursive residuals (CUSUM) and cumulative sum of recursive residuals squares (CUSUMSQ) tests as proposed by Brown, Durbin, and Evans (1975) was employed. The technique is appropriate for time series data and is recommended for use if one is uncertain about when a structural change might have taken place. The null hypothesis is that the coefficient vector &szlig; is the same every period. The CUSUM test is based on the cumulated sum of the residuals: &nbsp; &nbsp; &nbsp; (3.18) where &nbsp; &nbsp; (3.19) and &nbsp; &nbsp; (3.20) <strong>3.5&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sources of Data</strong> The Central bank of Nigeria served as the main source of data collection. This implies also that the study adopted secondary data. <strong>Chapter Four</strong> <strong>Empirical Results</strong> <strong>4.1&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Descriptive Statistics</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Before going into cointegration analysis, we will attempt to briefly examine the properties of the data with descriptive statistics. Table 4.1 and Figures 4.1 to 4.5 will be acknowledged for this purpose. Table 4.1: Descriptive Statistics &nbsp; PER_RGDP PER_PEE PENR SENR TENR Mean 264316.01 635.72 23096192.94 5796345.78 787115.08 Median 232704.55 361.03 19747039.31 4410684.33 755776.70 Maximum 385349.04 2340.12 46188979.59 11840028.21 1648670.36 Minimum 199039.15 7.38 9554076.94 1846106.82 49626.49 Std. Dev. 66113.04 681.06 9425336.46 3142601.76 592505.50 Skewness 0.65 0.77 0.59 0.79 0.17 Kurtosis 1.83 2.43 2.27 2.15 1.36 Jarque-Bera 4.88 4.24 3.01 5.14 4.47 Probability 0.09 0.12 0.22 0.08 0.11 Observations 38 38 38 38 38 &nbsp; Figure 4.1: Trend of Real Gross Domestic Product (RGDP) Per Capita &nbsp; &nbsp; &nbsp; Figure 4.2: Trend of Public Expenditure on Education (PEE) Per Capita &nbsp; &nbsp; Figure 4.3: Trend of Primary School Enrolment (PENR) &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Figure 4.4: Trend of Secondary School Enrolment (SENR) &nbsp; &nbsp; Figure 4.5: Trend of Tertiary School Enrolment (TENR) &nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; From the second column of Table 4.1, RGDP per capita mean is NGN 264, 316.01 ($734.21). This critically lags behind RGDP per capita mean in all developed (OECD) countries and underscores the need for human and non-human capital development. Further, RGDP per capita maximum is NGN 385, 349.04 while its minimum is NGN 199, 039.15. Given that the trend of RGDP per capita is positively sloped as seen in Figure 4.1, the disparity between RGDP per capita maximum and its minimum indicates growth in RGDP per capita during the period under investigation. Lastly, the Jarque-Bera statistic (4.88) and probability value (0.09) of RGDP per capita simply suggest that it follows a normal distribution, with NGN 66, 113.04 as its standard deviation. &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; From the third column of Table 4.1, PEE per capita mean is NGN 635.72 ($1.77). Just like RGDP per capita, this critically lags behind PEE per capita mean in all developed (OECD) countries and underscores the need for more government intervention in the education sector. Further, PEE per capita maximum is NGN 2, 340.12 while its minimum is NGN 7.38. Given that the trend of PEE per capita is positively sloped exponentially as seen in Figure 4.2, the disparity between PEE per capita maximum and its minimum indicates rapid growth in PEE per capita during the period under investigation. Lastly, the Jarque-Bera statistic (4.24) and probability value (0.12) of PEE per capita simply suggest that it follows a normal distribution, with NGN 681.06 as its standard deviation. From the fourth column of Table 4.1, PENR mean is 23096192.94. This represents about 18.33% of total population mean (126036036.63) and indicates high primary school enrolment during the period under investigation. Further, PENR maximum is 46188979.59 while its minimum is 9554076.94. Given that the trend of PENR is positively sloped linearly as seen in Figure 4.3, the disparity between PENR maximum and its minimum indicates consistent growth in PENR during the period under investigation. Lastly, the Jarque-Bera statistic (3.01) and probability value (0.22) of PENR simply suggest that it follows a normal distribution, with 9425336.46 as its standard deviation. From the fifth column of Table 4.1, SENR mean is 5796345.78. This represents about 4.60% of total population mean (126036036.63) and indicates relatively low secondary school enrolment during the period under investigation. Further, SENR maximum is 11840028.21 while its minimum is 1846106.82. Given that the trend of SENR is positively sloped exponentially as seen in Figure 4.4, the disparity between SENR maximum and its minimum indicates rapid growth in SENR during the period under investigation. Lastly, the Jarque-Bera statistic (5.14) and probability value (0.08) of SENR simply suggest that it follows a normal distribution, with 3142601.76 as its standard deviation. From the sixth column of Table 4.1, TENR mean is 787115.08. This represents about 0.63% of total population mean (126036036.63) and indicates very low tertiary school enrolment during the period under investigation. Further, TENR maximum is 1648670.36 while its minimum is 49626.49. Given that the trend of TENR is positively sloped concavely as seen in Figure 4.5, the disparity between TENR maximum and its minimum indicates slow growth in TENR during the period under investigation. Lastly, the Jarque-Bera statistic (4.47) and probability value (0.11) of TENR simply suggest that it follows a normal distribution, with 592505.50 as its standard deviation. From the descriptive statistics above, it is obvious that substantial disparities exist between the maximum and minimum values of the variables, especially for PEE per capita and TENR. This may distort the regression results of the cointegration analysis and may also lead to unnecessarily large regression coefficients. In order to avoid these problems, we have transformed the variables in two major ways. Firstly, we have reduced disparity among the variables by expressing PENR, SENR, and TENR as percentages of population total. Secondly, we have downsized all the variables to a smaller scale by expressing them in natural log form. Therefore instead of RGDP, PEE per capita, PENR, SENR, and TENR, we now have Ln_PER_RGDP, Ln_PER_PEE, Ln_PENR, Ln_SENR, and Ln_TENR respectively as our investigative variables. &nbsp; &nbsp; &nbsp; <strong>4.2&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Break-Point Unit Root Test Results</strong> Table 4.2: Break-Point Unit Root Test Result Summary Variables Lags Included Specification Break Date ADF Test Statistic 5% Critical Value Summary <em>Ln_PER_RGDP</em><em>_t</em> 0 Intercept &amp; Trend 2001 -3.3506 -5.1757 Non-Stationary <em>∆Ln_PER_RGDP</em><em>_t</em> 2 Intercept &amp; Trend 2001 -5.4176 -5.1757 Stationary <em>Ln_PER_PEE</em><em>_t</em> 0 Intercept &amp; Trend 2004 -3.3665 -5.1757 Non-Stationary <em>∆Ln_PER_PEE</em><em>_t</em> 5 Intercept &amp; Trend 1995 -5.6226 -5.1757 Non-Stationary <em>Ln_PENR</em><em>_t</em> 7 Intercept &amp; Trend 2004 -7.6901 -5.1757 Stationary <em>Ln_SENR</em><em>_t</em> 3 Intercept &amp; Trend 1998 -5.0584 -5.1757 Non-Stationary <em>∆Ln_SENR</em><em>_t</em> 3 Intercept &amp; Trend 2016 -6.4199 -5.1757 Stationary <em>Ln_TENR</em><em>_t</em> 1 Intercept &amp; Trend 1998 -6.9768 -5.1757 Stationary Note(s): Lag selection based on Schwarz Information Criterion (SIC) &nbsp; As seen in the above table, there are different orders of integration for the time-series variables. Specifically, <em>Ln_PENR</em> and <em>Ln_TENR</em> are stationary at levels, while others are stationary only at the first difference. The bounds cointegration method is more appropriate in this case because it permits the combination of stationary and difference-stationary time series. <strong>4.3&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ARDL Bounds Cointegration Test Results</strong> Table 4.3: Lag/Model Selection Criteria Table Number of Models Evaluated: 16 Dependent Variable: <em>Ln_PER_RGDP</em> S|N Model AIC Specification 1 16 -4.0889 ARDL(1, 0, 0, 0, 0) 2 15 -4.0552 ARDL(1, 0, 0, 0, 1) 3 12 -4.0477 ARDL(1, 0, 1, 0, 0) 4 14 -4.0448 ARDL(1, 0, 0, 1, 0) 5 8 -4.0445 ARDL(1, 1, 0, 0, 0) 6 11 -4.0212 ARDL(1, 0, 1, 0, 1) 7 13 -4.0121 ARDL(1, 0, 0, 1, 1) 8 10 -4.0118 ARDL(1, 0, 1, 1, 0) 9 7 -4.0066 ARDL(1, 1, 0, 0, 1) 10 6 -3.9994 ARDL(1, 1, 0, 1, 0) 11 4 -3.9970 ARDL(1, 1, 1, 0, 0) 12 9 -3.9894 ARDL(1, 0, 1, 1, 1) 13 3 -3.9672 ARDL(1, 1, 1, 0, 1) 14 5 -3.9626 ARDL(1, 1, 0, 1, 1) 15 2 -3.9589 ARDL(1, 1, 1, 1, 0) 16 1 -3.9357 ARDL(1, 1, 1, 1, 1) Note(s): * indicates chosen optimal lag specification based on the Akaike Information Criterion The Akaike criterion shows that ARDL(1, 0, 0, 0, 0) is the best lag specification for the ARDL model, thereby indicating that it is best to include only a single lag of the endogenous variable (<em>Ln_PER_RGDP</em>), and 0 lags of the other exogenous variables (<em>Ln_PER_PEE, Ln_PENR, Ln_SENR, </em>and <em>Ln_TENR</em>). On this basis, an ARDL model was estimated and the bounds cointegration method was applied to test for cointegration as seen in the following tables. Table 4.4: Auto Regressive Distributed Lag (ARDL) Model Estimates Dependent Variable: <em>Ln_PER_RGDP</em><em>_t</em> Regressors Coefficient Standard Error t-statistic Prob. <em>Ln_PER_RGDP _t-1</em> 0.723844 0.063884 11.33053 0.0000 <em>Ln_PER_PEE</em><em>_t</em> 0.006558 0.014438 0.454194 0.6529 <em>Ln_PENR</em><em>_t</em> 0.166945 0.048731 3.425881 0.0017 <em>Ln_SENR_t</em> 0.105751 0.044395 2.382033 0.0235 <em>Ln_TENR</em><em>_t</em> 0.033421 0.036354 0.919326 0.3650 <em>C</em> 2.80666 0.598588 4.688802 0.0001 &nbsp; Table 4.5: Bounds Cointegration Test &nbsp; Computed Wald (F-Statistic): 8.5420 10% level 5% level 2.5% level 1% level <em>k </em>= 4 I(0) I(1) I(0) I(1) I(0) I(1) I(0) I(1) <em>F</em>* 2.45 3.52 2.86 4.01 3.25 4.49 3.74 5.06 Source: Pesaran et al. <em>k</em> signifies the number of regressors <em>F</em>* corresponds to the model with unrestricted intercept and trend In the above table, the bounds test statistic (8.5420) surpasses the upper-bound (4.01) at the 5% level of significance and therefore leads to the rejection of the null hypothesis of &ldquo;no cointegration&rdquo;. Based on this result, a &ldquo;restricted&rdquo; error correction model was estimated as well as a long-run &lsquo;equilibrium&rsquo; model as seen in the subsequent tables and equations. Table 4.6a: Error Correction Model Dependent Variable: &Delta;<em> Ln_PER_RGDP</em><em>_t</em> Regressors Coefficient Standard Error t-statistic Prob. <em>∆Ln_PER_PEE</em><em>_t</em> 0.0065 0.0144 0.4541 0.6529 <em>∆Ln_PENR</em><em>_t</em> 0.1669 0.0487 3.4258 0.0017 <em>∆Ln_SENR</em><em>_t</em> 0.1057 0.0443 2.3820 0.0235 <em>∆Ln_TENR</em><em>_t</em> 0.0334 0.0363 0.9193 0.3650 <em>ECT _t-1</em> -0.2761 0.0638 -4.3227 0.0001 &nbsp; Table 4.6b: Long-Run Model Dependent Variable: <em>Ln_PER_RGDP</em><em>_t</em> Regressors Coefficient Standard Error t-statistic Prob. <em>Ln_PER_PEE</em><em>_t</em> 0.0237 0.0489 0.4850 0.6310 <em>Ln_PENR</em><em>_t</em> 0.6045 0.1253 4.8213 0.0000 <em>Ln_SENR</em><em>_t</em> 0.3829 0.1106 3.4602 0.0016 <em>Ln_TENR</em><em>_t</em> 0.1210 0.1500 0.8064 0.4261 <em>C</em> 10.1633 0.5757 17.6524 0.0000 &nbsp; In the error correction model, the error correction term (<em>ECT_t-1</em>) is expectedly negative and statistically significant at the 5% level (based on its <em>p</em>-value (0.0001)). Its magnitude (-0.2761) indicates a low but significant rate of adjustment to long-run equilibrium and specifically implies that approximately 27.61% of all discrepancies in long-run equilibrium will be corrected in each period. On the other hand, in the long-run model, the first long-run coefficient (<em>Ln_PER_PEE</em><em>_t</em>) is expectedly positive but its <em>p</em>-value (0.6310) indicates that it is statistically insignificant at the 5% level of significance, thereby implying that increment in <em>Ln_PER_PEE</em> will not cause <em>Ln_PER_RGDP</em> to increase. . Similarly, the fourth long-run coefficient (<em>Ln_TENR</em>) is expectedly positive but its <em>p</em>-value (0.4261) indicates that it is statistically insignificant at the 5% level of significance, thereby implying that increment in <em>Ln_TENR</em> will not cause <em>Ln_PER_RGDP</em> to increase. On the other hand, the second long-run coefficient (<em>Ln_PENR</em>) is expectedly positive and its <em>p</em>-value (0.0000) indicates that it is statistically significant at the 5% level of significance, thereby implying that increment in <em>Ln_PENR</em> will cause <em>Ln_PER_RGDP</em> to increase by 0.6045. Similarly, the third long-run coefficient (<em>Ln_SENR</em>) is expectedly positive and its <em>p</em>-value (0.0016) indicates that it is statistically significant at the 5% level of significance, thereby implying that increment in <em>Ln_SENR</em> will cause <em>Ln_PER_RGDP</em> to increase by 0.3829. The intercept also appears to be positive and statistically significant thereby indicating that the long-run model has a positive autonomous component measuring up to 10.1633 units. <strong>4.4&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Model Evaluation Results</strong> <strong>4.4.1&nbsp;&nbsp;&nbsp; Test of Goodness-of-Fit</strong> Table 4.7: Test of Goodness-of-Fit Summary Model R² Adj. R² ARDL Model 0.9875 0.9854 ECM 0.6948 0.6567 &nbsp; The adjusted R² of the ARDL model has a magnitude of 0.9854 and therefore implies that the ARDL model explains as much as 98.54% of the variation in its endogenous variable. Further, the adjusted R² of the ECM has a magnitude of 0.6567 and therefore implies that the error correction model (ECM) explains as much as 65.67% of the variation in its endogenous variable. <strong>4.4.2&nbsp;&nbsp;&nbsp; T-Test and F-Test</strong> Table 4.8: F-Test Summary Model F-Statistic 5% Critical Value Prob. Remarks ARDL Model 490.1238 F(5,31) = 2.52 0.0000 Jointly Significant @ 5% ECM 15.2700 F(4,32) = 2.67 0.0000 Jointly Significant @ 5% &nbsp; The F-statistic (490.1238) for the ARDL model exceeds its 5% critical value (2.66), thereby implying that the parameters of the ARDL model are jointly significant at the 5% level of significance. Further, the F-statistic (15.2700) of the ECM also exceeds its 5% critical value (2.84), thereby implying that the parameters of the error correction model (ECM) are jointly significant at the 5% level of significance. Table 4.9: T-Test Summary T-Test for the Long-Run Estimates Regressors t-statistic 5% Critical Value Remarks <em>Ln_PER_PEE</em><em>_t</em> 0.4850 1.9600 Insignificant <em>Ln_PENR</em><em>_t</em> 4.8213 1.9600 Significant <em>Ln_SENR</em><em>_t</em> 3.4602 1.9600 Significant <em>Ln_TENR</em><em>_t</em> 0.8064 1.9600 Insignificant <em>C</em> 17.6524 1.9600 Significant &nbsp; T-Test for the Error Correction Model (ECM) Estimates &nbsp; Regressors t-statistic 5% Critical Value Remarks &nbsp; <em>∆Ln_PER_PEE</em><em>_t</em> 0.4541 1.9600 Insignificant &nbsp; <em>∆Ln_PENR</em><em>_t</em> 3.4258 1.9600 Significant &nbsp; <em>∆Ln_SENR</em><em>_t</em> 2.3820 1.9600 Significant &nbsp; <em>∆Ln_TENR</em><em>_t</em> 0.9193 1.9600 Insignificant &nbsp; <em>ECT _t-1</em> -4.3227 1.9600 Significant &nbsp; &nbsp; In the long-run model, the t-statistics for the first and fourth parameters are less than the 5% critical value (1.96), thereby indicating that the first and fourth parameters are statistically insignificant at the 5% level of significance, while the t-statistic for the second, third, and fifth parameters are greater than the 5% critical value (1.96), thereby indicating that they are statistically significant at the 5% level of significance. Similarly, in the ECM, the t-statistics for the first and fourth parameters are less than the 5% critical value (1.96), thereby indicating that the first and fourth parameters are statistically insignificant at the 5% level of significance, while the t-statistic for the second, third, and fifth parameters are greater than the 5% critical value (1.96), thereby indicating that they are statistically significant at the 5% level of significance. <strong>Normality Test</strong> Table 4.10: Jarque-Bera Normality Test Summary Model Skewness Kurtosis JB Statistic Prob. ARDL Model -0.5558 2.8731 1.9297 0.3810 ECM -0.7369 2.9430 3.3544 0.1868 &nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; In the ARDL model, the <em>p</em>-value (0.3810) of the J-B test exceeds the 0.05 benchmark, and therefore indicates that the residuals of the ARDL model are normally distributed. Further, in the ECM, the <em>p</em>-value (0.1868) of the J-B test also exceeds the 0.05 benchmark, and therefore indicates that the residuals of the error correction model (ECM) are normally distributed. <strong>4.4.4&nbsp;&nbsp;&nbsp; Heteroskedasticity Test</strong> Table 4.11: Breusch-Pagan-Godfrey Heteroskedasticity Test Summary Model BPG Statistic (Obs*R-sq) Prob. ARDL Model 4.3085 0.5059 ECM 7.2979 0.1209 &nbsp; In the ARDL model, the <em>p</em>-value (0.5059) of the BPG test exceeds the 0.05 benchmark, and therefore indicates that the residuals of the ARDL model are homoskedastic. Similarly, in ECM, the <em>p</em>-value (0.1209) of the BPG test also exceeds the 0.05 benchmark, and therefore indicates that the residuals of the error correction model (ECM) are homoskedastic. <strong>4.4.5&nbsp;&nbsp;&nbsp; Autocorrelation Test</strong> Table 4.12: Breusch-Godfrey Serial Correlation Test Summary Model BG Statistic (Obs*R-sq) Prob. ARDL Model 0.1021 0.7493 ECM 0.8776 0.3488 &nbsp; In the ARDL model, the <em>p</em>-value (0.7493) of the BG test exceeds the 0.05 benchmark, and therefore indicates that the residuals of the ARDL model are not serially correlated. Similarly, in ECM, the <em>p</em>-value (0.3488) of the BG test also exceeds the 0.05 benchmark, and therefore indicates that the residuals of the error correction model (ECM) are not serially correlated. <strong>4.4.6&nbsp;&nbsp;&nbsp; Functional Specification Test</strong> Table 4.13: RESET Model Specification Test Summary Model Test Statistics Value Degrees of Freedom Prob. ARDL Model t-statistic 0.805722 30 0.4267 F-statistic 0.649189 (1, 30) 0.4267 ECM t-statistic 0.533837 31 0.5973 F-statistic 0.284982 (1, 31) 0.5973 &nbsp; In the ARDL model, the F-statistic <em>p</em>-value (0.4267) of the RESET test exceeds the 0.05 benchmark, and therefore indicates that the ARDL model was adequately specified. Further, in the ECM, the F-statistic <em>p</em>-value (0.5973) of the RESET test exceeds the 0.05 benchmark, and therefore indicates that the error correction model (ECM) was adequately specified. <strong>4.4.7&nbsp;&nbsp;&nbsp; CUSUMSQ Stability Test</strong> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The Cumulative Sum of Residuals (CUSUM) Squares test was used to examine the stability of the ARDL model. The result is captured in the following figure. Figure 4.6: CUSUMSQ Plot &nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; In interpreting the CUSUMSQ test, we may conclude that there is instability only if the CUSUMSQ plot falls outside the boundaries of the upper and lower dotted lines which signify the &ldquo;5% level of significance&rdquo;. In this regard, the plot of the CUSUMSQ test in the above figure shows that the ARDL model becomes momentarily unstable in year 2002. However, apart from 2002, the ARDL model appears to be stable in every other year as indicated by the confinement of the CUSUMSQ plot between the upper and lower dotted lines. Overall, considering the fact that this momentary period of instability does not coincide with any major event in Nigeria&rsquo;s education sector, we can conclude that instability is due to chance, and that the estimates of the model are reliable because apart from year 2002 the ARDL model appears to be stable.

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Introduction The year 2018 saw drastic shifts in fan spaces where fan works, such as art, fiction, and videos, were once widely, openly shared, including those containing sexually explicit content, a.k.a. porno. Major catalysts were the highly contested United States legislations Stop Enabling Sex Traffickers Act (SESTA) and Fight Online Sex Trafficking Act (FOSTA), which addressed the liability of host sites for content shared by users. Shortly after, similar legislation appeared around the world, including Australia’s Online Safety Act 2021. In response, Websites once popular with adolescents, which were well known for the proliferation of fan works, reconfigured their terms and conditions to exclude porno. This ousted previously thriving communities, especially lesbian, gay, bisexual, transgender, queer, and other related communities (LGBTQ+), who feared overcorrections would be exclusionary of content about sexuality and gender, broadly. This begs the questions, what drives this kind of legislation and how might it impact LGBTQ+ adolescents who often have fewer spaces for identity exploration? Building upon work by other researchers, this article asserts that there may even be potential benefits to the types of personalised and progressive pornos shared in online fan spaces, related specifically to identity development, sex education, and representation. Fandom and Porno Fan works make up a critical portion of the digital landscape that adolescents around the globe interact with every day. While not all fan works are pornos, sexually explicit material does exist on many platforms used by fans to share these transformative works (TW), including platforms which largely appeal to young people despite an overall mixed-age user base (McLelland 108–109). A fan work is considered transformative when it alters canonical events (what actually happened) in a franchise, or real life, in some meaningful way (Jenkins 47–48). TWs, unlike mainstream porno, have the benefit of being more personalisable, as they are created by fans, for fans, usually with some ability to interact with the material via embedded engagement features on the social media sites where works are hosted (McInroy and Craig, It’s Like 242–243). Also, unlike mainstream porno, fan-produced porno (FPP) has historically been created and shared by women, often utilising third-wave feminist critique to address sexual agency and shift away from the male gaze, thus creating more space for discussions about consent and sexual freedom (McLelland 111). FPP is additionally more likely to explore transformative elements that are more inclusive of LGBTQ+ content creators (McInroy et al. 632–633). While fan-produced TWs, including FPP, can be based on anything around which fandoms form, media properties most likely to inspire these works typically hold less connection to the real world, such as those based in fantasy, science fiction, and the supernatural (Hardin). This is because media properties already removed from reality more easily lend themselves to transformation. Further, the worldbuilding elements of these genres already address themes of body, agency, and belonging that women and LGBTQ+ fans are unlikely to find in other mainstream media, porno or otherwise. In spaces where adolescents are consuming FPP, they are not just passively being imprinted upon by sexually explicit material. Rather, adolescent fans contribute towards critical discussion and self-exploration via their own active production and distribution of porno through TWs (McLelland 103; McInroy and Craig, It’s Like 240). This differs from mainstream porno, which is produced by studios for adult-only audiences, often relying heavily on the male gaze and regressive tropes about sex, gender, and sexuality which do not explore agency, nor emotional or physical safety. This is not to lambast mainstream porno, simply to state that most of it is not produced with women or LGBTQ+ people’s specific wants and needs in mind. Mainstream porno, unlike fan works, is also not made with intent to heavily interact with its fans in the same way, in most cases. It certainly does not intend to interact with young fans, as that would clearly violate related legislation. There are porno conventions, just as there are pop-culture fan conventions, but fannish behaviour and critique is culturally distinct in both. FPP, by contrast, is both interactive and benefits from being about fictional characters, meaning it has the potential to subvert some, though not all, labour and obscenity laws (McLelland 109). Ostensibly, if the subjects of the work are not real, they cannot be exploited, creating a different ethical landscape from that of mainstream porno, including ethics related to consumption by minors. Fan-Produced Porno and Law Laws related to youth and porno are relatively new, showing up en masse in the 1970s and evolving based on contextual factors dictating the role of children in social life (McLelland 103–107). Legislation is also commonly intertwined with anti-porno social movements, with the dawn of laws against porno in the 1970s occurring, in part, through the split of anti-porno and pro-porno feminism (Bracewell). According to Lim et al., several academics have noted that “supporters of censorship of pornography historically have been more likely to be older, female, religious, sexually or politically conservative, more likely to show gender role stereotyping, and less likely to have ever seen pornography” (669). This is important because, as previously noted, fan works may be intended to directly challenge moralistic discourse in favour of third wave, pro-porno, feminist schools of thought, which tends to run counter to viewpoints of the above groups of people in every way except the overlap with higher interactivity of women. One of the first high-profile cases brought to court involved imagery fitting the definition of a TW. The image in question was a sexualised illustration of Rupert the Bear, a then-popular children’s character, published in Oz Magazine in an issue for young people by young people (McLelland 102–103). The artist, a fifteen-year-old boy, noted during the 1971 court case against the magazine’s editors that he drew it specifically as a countercultural statement designed to challenge the hypocrisy of the very adults it appeared to offend (McLelland 103). A major criticism of obscenity laws, in addition to being anti-feminist or anti-counterculture, is they are too contextual, and thus may over-reach without actually protecting youth at all (Al-Alosi 159), as was critiqued in the above case (McLelland). Consequently, recent attempts at legislation have focussed heavily on trafficking and other potential harms that are less politically divisive. The early 2000s and 2010s saw moral panics and Website-specific strikethroughs related to minors’ online citizenship and FPP (Hunting, McLelland), but without sweeping, associated legislation until 2018. While new laws were implemented throughout the world, over several years, the beginning of the end for Websites hosting FPP, specifically, started in the US with SESTA/FOSTA. The original intent of both acts was said to be reduction in human rights violations, specifically human trafficking. In her review of the history and implementation of SESTA/FOSTA, Cotterill notes that proponents claim exorbitant decreases in trafficking as a result of the legislation, yet fail to look at the full picture, ignoring ways in which business simply moved from one site to the next (28). She also points out the reality that the biggest drop came when Backpage.com, a main focus of the legislation, was taken down, something that occurred before SESTA/FOSTA were passed, accomplished through existing legal actions that did not require additional legislation. Despite this, similar laws were enacted elsewhere, including Australia’s Online Safety Act 2021. One of the Websites impacted upon the most by anti-porno and trafficking legislation around the globe was Tumblr. In 2018, Tumblr was one of the most heavily utilised sites for fanworks and LGBTQ+ communities (Byron 338–347). The implementation of SESTA/FOSTA led to Tumblr overhauling their terms and conditions to ban FPP (Pilipets &amp; Paasonen 472). While Tumblr does still exist at the time of writing this article, it no longer occupies the same space in the cultural milieu of fandom communities, which now favour newer sites like Archive of Our Own (Ao3) and Discord, with features created to bypass legislation (Floegel 90). While these sites evolved to subvert government censorship, it is important to note that their design approaches do not always do well to protect adolescents against other potentially harmful biopolitics, such as racism (Floegel 92). More recent debate about laws impacting on FPP, especially in online spaces, centres on laws which target the use of fictional characters specifically. Given that TWs, by definition, utilise pre-existing characters and sometimes depictions of real people, it is difficult to detangle fan works from the intended target of many of these laws, which have largely arisen in response to anonymous deep-fakes, or other imagery created using artificial intelligence (Popova, Reading). Certainly, there are ethical dilemmas worthy of public and legal debate with regards to the likenesses of celebrities and other public figures, used without permission, in sexually explicit renderings. However, when overly restrictive laws are put into place, especially with regards to fictional characters, adults may, intentionally or unintentionally, limit the agency of young people and adults alike to engage in meaningful social commentary and discourse (McLelland 113–115). Retrospective analysis of existing laws also suggests that they are largely ineffective due to underutilisation, as well as legal loopholes that stop prosecutors from successfully charging social media and Internet sites (Cotterill 27–28). Further, sex workers’ rights and advocacy groups assert that SESTA/FOSTA do more harm than good, taking down Websites these workers use to maintain social networks which can be leveraged to improve safety on the job (Cotterill 28). Legislation also does not appear to recognise, nor express interest in, the voices of young people in online content creation and dissemination, creating legislation based on dominant moral interests of adults as opposed to seeking evidentiary support of real harm (McLelland 107–114). Investigating Harms of Porno Perhaps one of the most important questions about porno, including FPP, is whether it actually causes harm, necessitating legislation. Attwood et al. note relatively little academic evidence that access to porno is universally harmful to young people, and identify ways anti-porno discourse misses opportunities to delve into responsible consumption as part of normative sexual development (3753). In a systematic review, Vertongen et al. found that “research has functioned under highly homogenised presumptions about adolescent pornography use and its effects”, meaning results about the potential harms of porno are inconclusive at best (430). These authors discuss that what has been found suggests that adolescent engagement with porno is variable across time, as well as interrelated with sexual and social maturation (433). They also note that, while some adolescents appear to use porno to inform real-life sex practices, this is not without the same speculation and critique used by adults who purport youth need to be protected from that which they do not yet understand (438). On the contrary, youth seem to understand the difference between porno and real-life sex just fine. Lastly, the authors note that when harm is present in the research, it is most often correlated with pre-existing comorbidities and dispositions in relation to violent behaviors (436). In other words, some young people probably shouldn’t consume violent porno, but risk is most prevalent for those who are already predisposed to enact violence for other reasons. There does appear to be some correlation between age of first sex and exposure to porno, though in a recent systematic analysis, Pathmendra et al. explain that most studies showing this contain substantial enough limitations, in both design and measurement, that causal inference cannot be made (5). It is also important to consider what young people themselves are saying about porno. In a synthesis of thirty qualitative studies on young people and porno, Peterson et al. found use of porno by young people was considered normative, with utilities related to “pleasure, information, and instruction in the absence of sufficient sexuality education” (171). Distress caused by porno was specific to microaggressive, misogynistic, and violent content (195). Youth in the studies analysed reported a lack of spaces to discuss what they viewed with trusted adults, thus leaving little room for corrective experiences when harm did occur (195). To be clear, the issue here was not consumption of porno, but the inability to then discuss with trusted adults. According to Lim et al., in a survey of Australian youth, the majority do believe in some, reasonable legislation, and do recognise that pornography may be harmful to some, but not all, people (668). The majority of support for legislation in the study centred on reducing depictions of violence and increasing the visible use of safer sex practices (668). It should be noted that violence is sometimes a recurring theme in certain genres of FPP. However, in many cases, violence in these pornos is more contextualised (Popova, Dubcon) than it would be in mainstream porno, and can be largely avoided by utilising filters on newer host sites. With little evidence of universal harm caused by porno, one might ask a secondary question – whether social media, through which FPP is shared, are harmful. Despite popular discourse suggesting they are, research findings are nuanced. According to Valkenburg et al., there is some consensus that active social media use (e.g., engagement) may have benefits over passive social media use (e.g., scrolling), with passive social media use being more apt to cause harm (530–531). Similar to studies about the harms of pornography, however, these authors note that studies about social media use are theoretically flawed and fail to capture the full scope and diversity of use (544). In a qualitative investigation of social media use by young people in Australia, Cooper et al. note scholarly work recognising that “adolescents and young adults develop their identities, aspirations, social supports, and autonomy via online social networks, and nurture intimate peer relationships” (536). These authors also note that online and offline relationships appear interrelated (549–551). All this suggests that social media, like porno, may be playing a normative role in the lives of adolescents, which adults should seek to better understand as opposed to broadly legislating against. Investigating Benefits of Fan Produced Porno One potential benefit of FPP is its utility as an educational tool, especially among LGBTQ+ young people. Delmonaco and Haimson found that youth already rely on online spaces, such as those containing FPP, to obtain accurate information about sexual health (832). Gameson et al. investigated the roles of online sex self-education by teens through use of porno vs. classroom education, and found that while straight participants were more likely to search for information on pleasure and entertainment, LGBTQ+ teens were more likely to search for information related to identity discovery, confirmation, and affirmation, things not necessarily covered by school curriculum on sex education (461). Importantly, teens in this study also explored material within both spheres in dynamic ways which built off one another (481–484). This suggests a role for FPP as a dynamic tool, rather than an obstacle to formal education. McInroy et al. found additional evidence that LGBTQ+ youth utilise online fandoms to more safely explore identities, as well as challenge/transform popular narratives about identities, both through social media discourse and TWs such as FPP. McInroy and Craig found LGBTQ+ youth who participate in fandom also reach identity milestones earlier and quicker and use a broader variety of sexual and gender identity labels (Online 187–191). Further, due to widespread challenges to healthcare access for LGBTQ+ youth, social networks like these appear to be important in circumventing geopolitics in order to receive necessary health care (Edenfield et al.). Dym et al. found that online fanfic spaces also self-organise in a way that supports trauma recovery through the construction of shared narratives, thus additionally offering a structure for informal mental health support (5). Through qualitative analysis of 3,665 survey respondents, McInroy et al. discovered that, while imperfect, those engaged in online fandom communities found they offered more realistic depictions of queer life and sex than mainstream media (637–638). Using the same data set, McInroy and Craig found that fandom specifically offered LGBTQ+ people safe, customisable experiences which greatly benefit this marginalised population (It’s Like 239–240). These authors noted, even for those who reported fandom did not contribute to LGBTQ+ identity development, fandom participation was seen as valuable (242). Transgender and gender-diverse people specifically appear, through fandom communities and TWs, to explore beyond the “wrong body narrative” to more holistically explore body politics and transgressive experiences of bodies not otherwise represented broadly in media or the classroom (Duggan &amp; Fasekas). This ability to safely explore has real-world implications that translate into medical and mental health interventions, which often rely on an individual’s ability to explore gender and body in order to make informed medical decisions. There also appears to be a broader societal benefit to FPP. Enriquez and Lippert argue FPP is worthy of both study and archiving, especially given the role of women and gender-diverse people in producing content which presents important dialogues about sexuality and gender, and unquestionably contributes to the proliferation of genres like science fiction in popular media. They specifically cite how once-banned pornographies in the US are now considered commodities among book archivists, arguing that FPP has similar cross-cultural value as an artifact (193). Like others, they note ways in which fandoms increase diverse representation through the production of fan works, something Cook and Joseph note can translate into real-world fan activism that results in changes to mainstream media (56–57). Conclusion With little evidence of widespread harm caused by porno broadly, and emerging evidence of the importance of FPP in normative development, education, and representation in the digital age, especially for LGBTQ+ youth, legislators and researchers alike should consider who the rule of law in anti-porno legislation is really protecting. We encourage more reasonable legislation and other safeguards based on evidence, not emotions, drawing on needs expressed by young people themselves, who should be seen as both active consumers and producers of FPP. To accomplish this, better research is needed which considers nuances of porno use, the role of TWs, and the collective perspectives of adolescents who engage with porno. 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If we consider learning as a meaning-making process where people construct shared knowledge, it becomes a social dialogical activity in which knowledge is the result of an active process of articulation and reflection within a context (Jonassen et al.). An important element of this belief is that conversation is at the core of learning because knowledge is language-mediated. Within this context, what makes a conversation worthwhile and meaningful is how it is structured, how it is managed by the participants, and most importantly, how it is understood. In particular, conversation is essential in learning situations where the main goal is to generate a new understanding of the world (Bruner). Thus, if conversations can be seen as support for learning processes, the question then becomes how synchronous textual spaces mediate conversation and how chat affects learning. Experienced Teachers Learning in a Collaborative Virtual Environment We studied two different groups of experienced teachers from Kindergarten to Grade 12 (K-12) attending a Master of Education course entitled "Curriculum and Instruction". They communicated through a collaborative virtual environment (CVE) designed to enhance teachers' professional development: TAPPED IN™ (TI). We recorded their on-line conversations over six weeks. The teachers met twice a week for a two hour session and the data collected consisted of approximately 350-400 pages of text from transcripts. The following concerns, gleaned from an ongoing analysis of on-line conversations are of interest for this paper: The first concern has to do with the ability of teachers to concentrate on a task while managing multiple simultaneous conversations. The question is how to maintain the focus on the purpose of the goal oriented task. The second concern is related to the technical characteristics of a CVE and the teachers' feelings of being lost, too slow, or not understanding the point of the discussion. The question is how to deal with this confusion when the aim is to construct meanings from online discussion? The third concern is related the preceding points. It is concerned with the importance of a leader coaching and guiding experienced teachers online. We examined these three concerns, using TI during the teachers' on line discussions. Our primary goal in the analysis was to determine i) whether the teachers could conduct their learning activities through TI and ii) how goal-oriented conversations might be affected by the constraints of TI. The following examples come from a personal recorder. Messages are numbered in order to show their position in the session and to show the distance between the messages sent. Implications of Multitasking in Learning Sessions In CVEs, participants have the possibility of performing several tasks simultaneously (Holmevik). This is especially true when participants hold more than one conversation at a time. Participants can talk to one person or to the whole group while also chatting privately with people in the same CVE's room, in the same CVE or even in other CVEs. But the possibility of being able to participate in multiple conversations becomes potentially confusing and disorienting for teachers wanting to achieve a specific task. Let us give an example of how a main task (e.g. to share notes of pedagogical projects -- task 1) fragments into different tasks (e.g. learning a command -- how to create a note -- task 2; and socialise, express feelings and play with cows -- task 3). (Note that the students are in fact experienced teachers and a teacher is leading the session. The goal of the on-line session is to read and discuss the different educational projects that the students should have written in virtual notes.) The goal of the task became difficult to accomplish for teachers who were suddenly involved in more than one task at a time. In order to understand what is going on in this situation, participants had to accomplish extra work. They needed to filter messages and rank them to make the main objective of the session clear. In a goal-oriented session such as this, it is extremely important to keep track of the task as well as to concentrate on one activity at time. This entails a necessity to understand current threads in order to contribute to the object of interest for them as individuals and as a group member. Implications of Multi Threads and Floor-Taking in Goal-Oriented Conversations Perseverance with each message creates a parallelism that can become extremely disorienting to participants who intend to produce new understandings and not just maintain an awareness during on-line conversations. The larger the number of participants in a conversation, the more likely it is for fragmentation to occur. The jumbled and quickly scrolling screen can be quite disconcerting. Yet as mentioned by Mynatt et al., even between two participants, multi-threading is common due to the overlapping composition of conversational turns. Participants write simultaneously and the host computer sends the messages out sequentially. Under these conditions, competing conversational threads emerge continuously. It becomes difficult to know who actually holds the floor at the time. Here is an example showing a teacher -- student 2 -- looking for attention and trying to read and understand others' answers to his questions: Student 2 did not read message 26 sent from the teacher with care. In fact, the teacher did explain that there is a part in the assignment where students have to meet in order to exchange ideas about individual projects. Yet although S2's question was answered, S2 still did not understand. A possible reason is that S2 could have been focussed on writing the next question. Again, the teacher answered the question asked in message 29. However, S2 still did not understand in spite of S15 and S6 confirming that the teacher had already covered the question. Student 2 finally understood when the teacher addressed him directly and repeated what the other students had said before. In order to be heard, the students repeated their questions until they had the answer from the teacher. With more than a handful of participants, this attention seeking strategy may make on-line conversations confusing. Goal-oriented conversations then easily degenerate, as mentioned by Colomb and Simutis. These authors point out that one of the most common problems in using CMC is keeping students on task. Even experienced teachers do not escape from the possibility of converting from an instrumental discussion to a social one due to different misunderstanding between interlocutors. To be able to 'send' a message is not equivalent to claiming the 'floor'. An important extra task that teachers have to do in CVEs before sending a message is to think about how it meets the goal of the discussion. Looking for coherence and understanding is a must in learning situations and this becomes a great challenge in online learning sessions. On the other hand, different modalities of communication in CVEs may add richness and depth to online conversations when participants can anticipate constraints. Consider another group of teachers. They are discussing readings, and make great use of multiple modalities, such as gestures, to reframe misunderstandings. These gestures provide back channel information and other visual signs. Here is one example of what a group of teachers does in order to avoid embarrassing situations. As Mynatt et al. express, "the availability of multiple modalities gives complexity to the interactional rhythm, because people have choices about what modality to use at any particular moment and for any set of conversation partners" (138). Given these pros and cons of CVEs, the challenge of holding an on-line educational discussion requires the teachers to reestablish the context and control the underlying the sense of the conversation. This challenge could be also regarded as an exigency of the medium that 'invites' teachers to structure their conversations in order to encourage meaningful discussions. Importance of a Teacher of Teachers The problems mentioned earlier may be solved more easily when there is a leader at hand. Since these difficulties mainly arise at the start of learning the communication environment, it might be proposed that a leader is most critical in this phase. A comparison of two groups' interactions with and without a leader supports the intuition that a leader is crucial for keeping the learning on track even though the participants are experienced teachers. In this example, the task that the group performed was the same: "learning to attach an icon to their ellipses representing their presence in the system". Table 1. Data related to groups with and without a teacher Groups Learners Icons attached Messages produced Time employed 1. Without leader 12 0 549 56 min 8 sec 2. With leader 9 4 644 1h 27min 52 sec Fig. 1 Comparing flow and categories of the messages sent by the groups These frequencies confirm that teachers without a leader have more problems than the group with a leader. The number of successful icons attached by the groups (0 and 4 icons) demonstrates this claim. What happens is that the number of messages related to 'Task' decrease and those related to 'Relation' increase when there is no leader present -- a result which would be unsurprising among most people who have worked in 'real' classrooms. Messages produced and coded as 'Playing' and 'Feedback' also show a considerable difference between groups. Finally, categories such as 'Whisper' and 'Artifact' present in comparison to the others minimal differences between groups. A leader is a must for the smooth development of on-line conversation. The leader is a sort of mediator between the pedagogical task of the on-line conversation and what appears on the screen. The leader's task is to show which threads are important to follow or not and how messages should be read on the screen. Like an orchestra conductor, the leader coordinates tasks and makes sense of individual actions which are part of a common product and the quality of the on-going conversation. Discussion This ongoing research has demonstrated three important concerns surrounding experienced teachers' professional use of CVE. First, teachers chatting online have to anticipate the lack of assurance "that what gets sent gets read" and that gaining the floor in a CVE is "that one's message draws a response and in some way affect the direction of a current thread" (Colomb and Simutis). Teachers have to learn to negotiate turn-taking sequences behind the screen. When chatting, a person's intention to speak is not signalled. Overlapping and interruptions do not exist and non-verbal communication requires knowledge of gesture commands. Negotiating turns in online conversations is concerned with how people express information and what they express. In educational discussion, turns are generally taken when messages either present a good formulation of ideas, express controversial thinking, raise an issue that allows someone else to participate, or provide knowledge on the topic at hand. Second, teachers should learn to collaborate in online conversations. It is essential to be aware that people are writing a text while they discuss. The quality of the conversation will depend on one hand, how teachers manage the discussion and, on the other hand, the opinions they elaborate together. Third, teachers need leaders in online discussions. A leader has to be able to anticipate the text that the participants are writing. The leader has the responsibility of meeting pedagogical goals with a participant's messages. The leader has to show the coherence or incoherence of the discussion and raise issues that improve the level of the written interaction. These issues are extremely important in a context where people learn through conversations. As Laurillard has mentioned, "academic knowledge relies heavily on symbolic representation as the medium through which it is known. ... Students have to learn to handle the representations system as well as the ideas they represent" (27). Therefore, it is necessary that learners know and think about the rules of online discussion in order to adapt technical commands and effects to their needs. But these rules are in contrast to what participants expect from online conversations. Teachers want to perform their tasks with support of a computer program; they do not want to learn the computer program per se. CMC in learning activities must be based, not on visionary claims about technology as an all-purpose tool for automatic teaching/learning, but on specific accounts of how and why the technology affects the user's achievement of specific goals. Acknowledgements This study has been supported by a grant from the Swedish Transport &amp; Communication Research Board. We wish to express our gratitude to Judi Fusco, who, in several ways, has been a bridge between the TI community and us. We also want to thank the teachers, CharlesE and FlorenceE, for having the courage of letting Tessy 'sit in' on the sessions. The 'expert' session was lead by TerryG, whom we also want to thank for her generosity. Susan Wildermuth came to us in the final spurt, and we owe her much for the reliability check, structuring of ideas, and hints about related research. Finally, all students struggling with TI are thanked for their willingness to participate in this study. References Cherny, L. 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“What's the brief?” is an everyday question within the graphic design process. Moreover, the concept and importance of a design brief is overtly understood well beyond design practice itself—especially among stakeholders who work with designers and clients who commission design services. Indeed, a design brief is often an assumed and expected physical or metaphoric artefact for guiding the creative process. When a brief is lacking, incomplete or unclear, it can render an already ambiguous graphic design process and discipline even more fraught with misinterpretation. Nevertheless, even in wider design discourse, there appears to be little research on design briefs and the briefing process (Jones and Askland; Paton and Dorst). It seems astonishing that, even in Peter Phillips’s 2014 edition of Creating the Perfect Design Brief, he feels compelled to comment that “there are still no books available about design briefs” and that the topic is only “vaguely” covered within design education (21). While Phillips’s assertion is debatable if one draws purely from online vernacular sources or professional guides, it is supported by the lack of scholarly attention paid to the design brief. Graphic design briefs are often mentioned within design books, journals, and online sources. However, this article argues that the format, function and use of such briefs are largely assumed and rarely identified and studied. Even within the broader field of design research, the tendency appears to be to default to “the design brief” as an assumed shorthand, supporting Phillips’s argument about the nebulous nature of the topic. As this article contextualises, this is further problematised by insufficient attention cast on graphic design itself as a specific discipline. This article emerges from a wider, multi-stage creative practice study into graphic design practice, that used experimental performative design research methods to investigate graphic designers’ professional relationships with stakeholders (Meron, Strangely). The article engages with specific outcomes from that study that relate to the design brief. The article also explores existing literature and research and argues for academics, the design industry, and educationalists, to focus closer attention on the design brief. It concludes by suggesting that experimental and collaborative design methods offers potential for future research into the design brief. Contextualising the Design Brief It is critical to differentiate the graphic design brief from the operational briefs of architectural design (Blyth and Worthington; Khan) or those used in technical practices such as software development or IT systems design, which have extensive industry-formalised briefing practices and models such as the waterfall system (Petersen et al.) or more modern processes such as Agile (Martin). Software development and other technical design briefs are necessarily more formulaically structured than graphic design briefs. Their requirements are generally empirically and mechanistically located, and often mission-critical. In contrast, the conceptual nature of creative briefs in graphic design creates the potential for them to be arbitrarily interpreted. Even in wider design discourse, there appears to be little consistency about the form that a brief takes. Some sources indicate that a brief only requires one page (Elebute; Nov and Jones) or even a single line of text (Jones and Askland). At other times briefs are described as complex, high-level documents embedded within processes which designers respond to with the aim of producing end products to satisfy clients’ requirements (Ambrose; Patterson and Saville). Ashby and Johnson (40) refer to the design brief as a “solution neutral” statement, the aim being to avoid preconceptions or the narrowing of the creative possibilities of a project. Others describe a consultative (Walsh), collaborative and stakeholder-inclusive process (Phillips). The Scholarly Brief Within scholarly design research, briefs inevitably manifest as an assumed artefact or process within each project; but the reason for their use or antecedents for chosen formats are rarely addressed. For example, in “Creativity in the Design Process” (Dorst and Cross) some elements of the design brief are described. The authors also describe at what stage of the investigation the brief is introduced and present a partial example of the brief. However, there is no explanation of the form of the brief or the reasons behind it. They simply describe it as being typical for the design medium, adding that its use was considered a critical part of addressing the design problem. In a separate study within advertising (Johar et al.), researchers even admit that the omission of crucial elements from the brief—normally present in professional practice—had a detrimental effect on their results. Such examples indicate the importance of briefs for the design process, yet further illustrating the omission of direct engagement with the brief within the research design, methodology, and methods. One exception comes from a study amongst business students (Sadowska and Laffy) that used the design brief as a pedagogical tool and indicates that interaction with, and changes to, elements of a design brief impact the overall learning process of participants, with the brief functioning as a trigger for that process. Such acknowledgement of the agency of a design brief affirms its importance for professional designers (Koslow et al.; Phillips). This use of a brief as a research device informed my use of it as a reflective and motivational conduit when studying graphic designers’ perceptions of stakeholders, and this will be discussed shortly. The Professional Brief Professionally, the brief is a key method of communication between designers and stakeholders, serving numerous functions including: outlining creative requirements, audience, and project scope; confirming project requirements; and assigning and documenting roles, procedures, methods, and approval processes. The format of design briefs varies from complex multi-page procedural documents (Patterson and Saville; Ambrose) produced by marketing departments and sent to graphic design agencies, to simple statements (Jones and Askland; Elebute) from small to medium-sized businesses. These can be described as the initial proposition of the design brief, with the following interactions comprising the ongoing briefing process. However, research points to many concerns about the lack of adequate briefing information (Koslow, Sasser and Riordan). It has been noted (Murray) that, despite its centrality to graphic design, the briefing process rarely lives up to designers’ expectations or requirements, with the approach itself often haphazard. This reinforces the necessarily adaptive, flexible, and compromise-requiring nature of professional graphic design practice, referred to by design researchers (Cross; Paton and Dorst). However, rather than lauding these adaptive and flexible designer abilities as design attributes, such traits are often perceived by professional practitioners as unequal (Benson and Dresdow), having evolved by the imposition by stakeholders, rather than being embraced by graphic designers as positive designer skill-sets. The Indeterminate Brief With insufficient attention cast on graphic design as a specific scholarly discipline (Walker; Jacobs; Heller, Education), there is even less research on the briefing process within graphic design practice (Cumming). Literature from professional practice on the creation and function of graphic design briefs is often formulaic (Phillips) and fractured. It spans professional design bodies, to templates from mass-market printers (Kwik Kopy), to marketing-driven and brand-development approaches, in-house style guides, and instructional YouTube videos (David). A particularly clear summary comes from Britain’s Design Council. This example describes the importance of a good design brief, its requirements, and carries a broad checklist that includes the company background, project aims, and target audience. It even includes stylistic tips such as “don’t be afraid to use emotive language in a brief if you think it will generate a shared passion about the project” (Design Council). From a subjective perspective, these sources appear to contain sensible professional advice. However, with little scholarly research on the topic, how can we know that, for example, using emotive language best informs the design process? Why might this be helpful and desirable (or otherwise) for designers? These varied approaches highlight the indeterminate treatment of the design brief. Nevertheless, the very existence of such diverse methods communicates a pattern of acknowledgement of the criticality of the brief, as well as the desire, by professional bodies, commentators, and suppliers, to ensure that both designers and stakeholders engage effectively with the briefing process. Thus, with such a pedagogic gap in graphic design discourse, scholarly research into the design brief has the potential to inform vernacular and formal educational resources. Researching the Design Brief The research study from which this article emerges (Meron, Strangely) yielded outcomes from face-to-face interviews with eleven (deidentified) graphic designers about their perceptions of design practice, with particular regard to their professional relationships with other creative stakeholders. The study also surveyed online discussions from graphic design forums and blog posts. This first stage of research uncovered feelings of lacking organisational gravitas, creative ownership, professional confidence, and design legitimacy among the designers in relation to stakeholders. A significant causal factor pointed to practitioners’ perceptions of lacking direct access to and involvement with key sources of creative inspiration and information; one specific area being the design brief. It was a discovery that was reproduced thematically during the second stage of the research. This stage repurposed performative design research methods to intervene in graphic designers’ resistance to research (Roberts, et al), with the goal of bypassing practitioners’ tendency to portray their everyday practices using formulaic professionalised answers (Dorland, View). In aiming to understand graphic designers’ underlying motivations, this method replaced the graphic designer participants with trained actors, who re-performed narratives from the online discussions and designer interviews during a series of performance workshops. Performative methodologies were used as design thinking methods to defamiliarise the graphic design process, thereby enabling previously unacknowledged aspects of the design process to be unveiled, identified and analysed. Such defamiliarisation repurposes methods used in creative practice, including design thinking (Bell, Blythe, and Sengers), with performative elements drawing on ethnography (Eisner) and experimental design (Seago and Dunne). Binding these two stages of research study together was a Performative Design Brief—a physical document combining narratives from the online discussions and the designer interviews. For the second stage, this brief was given to a professional theatre director to use as material for a “script” to motivate the actors. In addition to identifying unequal access to the creative process as a potential point of friction, this study yielded outcomes suggesting that designers were especially frustrated when the design brief was unclear, insufficiently detailed, or even missing completely. The performative methodology enabled a refractive approach, using performative metaphor and theatre to defamiliarise graphic design practice, portraying the process through a third-party theatrical prism. This intervened in graphic designers’ habitual communication patterns (Dorland, The View). Thus, combining traditional design research methods with experimental interdisciplinary ones, enabled outcomes that might not otherwise have emerged. It is an example of engaging with the fluid, hybrid (Heller, Teaching), and often elusive practices (van der Waarde) of graphic design. Format, Function, and Use A study (Paton and Dorst) among professional graphic designers attempts to dissect practitioners’ perceptions of different aspects of briefing as a process of ‘framing’. Building on the broader theories of design researchers such as Nigel Cross, Bryan Lawson, and Donald Schön, Paton and Dorst suggest that most of the designers preferred a collaborative briefing process where both they and client stakeholders were directly involved, without intermediaries. This concurs with the desire, from many graphic designers that I interviewed, for unobstructed engagement with the brief. Moreover, narratives from the online discussions that I investigated suggest that the lack of clear frameworks for graphic design briefs is a hotly debated topic, as are perceptions of stakeholder belligerence or misunderstanding. For example, in a discussion from Graphic Design Forums designer experiences range from only ever receiving informal verbal instructions—“basically, we’ve been handed design work and they tell us ‘We need this by EOD’” (VFernandes)—to feeling obliged to pressure stakeholders to provide a brief—“put the burden on them to flesh out the details of a real brief and provide comprehensive material input” (HotButton) —to resignation to an apparent futility of gaining adequate design briefs from stakeholders because— “they will most likely never change” (KitchWitch). Such negative assumptions support Koslow et al.’s assertion that the absence of a comprehensive brief is the most “terrifying” thing for practitioners (9). Thus, practitioners’ frustrations with stakeholders can become unproductive when there is an inadequate design brief, or if the creative requirements of a brief are otherwise removed from the direct orbit of graphic designers. This further informs a narrative of graphic designers perceiving some stakeholders as gatekeepers of the design brief. For example, one interviewed designer believed that stakeholders ‘don’t really understand the process’ (Patricia). Another interviewee suggested that disorganised briefs could be avoided by involving designers early in the process, ensuring that practitioners had direct access to the client as a creative source, rather than having to circumnavigate stakeholders (Marcus). Such perceptions appeared to reinforce beliefs among these practitioners that they lack design capital within the creative process. These perceptions of gatekeeping of the design brief support suggestions of designers responding negatively when stakeholders approach the design process from a different perspective (Wall and Callister), if stakeholders assume a managerial position (Jacobs) and, in particular, if stakeholders are inexperienced in working with designers (Banks et al.; Holzmann and Golan). With such little clarity in the design briefing process, future research may consider comparisons with industries with more formalised briefing processes, established professional statuses, or more linear histories. Indeed, the uneven historical development of graphic design (Frascara; Julier and Narotzky) may influence the inconsistency of its briefing process. Inconsistency as Research Opportunity The inconsistent state of the graphic design brief is reflective of the broader profession that it resides within. Graphic design as a profession remains fluid and inconsistent (Dorland, Tell Me; Jacobs), with even its own practitioners unable to agree on its parameters or even what to call the practice (Meron, Terminology). Pedagogically, graphic design is still emerging as an independent discipline (Cabianca; Davis), struggling to gain capital outside of existing and broader creative practices (Poynor; Triggs). The inherent interdisciplinarity (Harland) and intangibility of graphic design also impact the difficulty of engaging with the briefing process. Indeed, graphic design’s practices have been described as “somewhere between science and superstition (or fact and anecdote)” (Heller, Teaching par. 3). With such obstacles rendering the discipline fractured (Ambrose et al.), it is understandable that stakeholders might find engaging productively with graphic design briefs challenging. This can become problematic, with inadequate stakeholder affinity or understanding of design issues potentially leading to creative discord (Banks et al.; Holzmann and Golan). Identifying potentially problematic and haphazard aspects of the design brief and process also presents opportunities to add value to research into broader relationships between graphic designers and stakeholders. It suggests a practical area of study with which scholarly research on collaborative design approaches might intersect with professional graphic design practice. Indeed, recent research suggests that collaborative approaches offer both process and educational advantages, particularly in the area of persona development, having the ability to discover the “real” brief (Taffe 394). Thus, framing the brief as a collaborative, educative, and negotiative process may allow creative professionals to elucidate and manage the disparate parts of a design process, such as timeframes, stakeholders, and task responsibilities, as well as the cost implications of stakeholder actions such as unscheduled amendments. It can encourage the formalisation of incomplete vernacular briefs, as well as allow for the influence of diverse briefing methods, such as the one-page creative brief of advertising agencies, or more formal project management practices while allowing for some of the fluidity of more agile approaches: acknowledging that changes may be required while keeping all parties informed and involved. In turn, collaborative approaches may contribute towards enabling the value of contributions from both graphic designers and stakeholders and it seems beneficial to look towards design research methodologies that promote collaborative pathways. Mark Steen, for example, argues for co-design as a form of design thinking for enabling stakeholders to combine knowledge with negotiation to implement change (27). Collaborative design methods have also been advocated for use between designers and users, with stakeholders on shared projects, and with external collaborators (Binder and Brandt). Others have argued that co-design methods facilitate stakeholder collaboration “across and within institutional structures” while challenging existing power relations, albeit leaving structural changes largely unaffected (Farr 637). The challenge for collaborative design research is to seek opportunities and methodologies to conduct design brief research within a graphic design process that often appears amorphous, while also manifesting complex designer–stakeholder dynamics. Doubly so, when the research focus—the graphic design brief—often appears as nebulous an entity as the practice it emerges from. Conclusion The research discussed in this article suggests that graphic designers distrust a creative process that itself symbolises an inconsistent, reactive, and often accidental historical development of their profession and pedagogy. Reflecting this, the graphic design brief emerges almost as a metaphor for this process. The lack of overt discussion about the format, scope, and process of the brief feeds into the wider framework of graphic design’s struggle to become an independent scholarly discipline. This, in turn, potentially undermines the professional authority of graphic design practice that some of its practitioners believe is deficient. Ultimately, the brief and its processes must become research-informed parts of graphic design pedagogy. Embracing the brief as a pedagogical, generative, and inseparable part of the design process can inform the discourse within education, adding scholarly value to practice and potentially resulting in increased agency for practitioners. The chameleon-like nature of graphic design’s constant adaptation to ever-changing industry requirements makes research into the role and influences of its briefing process challenging. Thus, it also follows that the graphic design brief is unlikely to quickly become as formalised a document or process as those from other disciplines. But these are challenges that scholars and professionals must surely embrace if pedagogy is to gain the research evidence to influence practice. As this article argues, the often obfuscated practices and inherent interdisciplinarity of graphic design benefit from experimental research methods, while graphic designers appear responsive to inclusive approaches. Thus, performative methods appear effective as tools of discovery and collaborative methodologies offer hope for organisational intervention. References Ambrose, Gavin. Design Thinking for Visual Communication. Fairchild, 2015. Ambrose, Gavin, Paul Harris, and Nigel Ball. The Fundamentals of Graphic Design. Bloomsbury, 2020. Ashby, M.F., and Kara Johnson. Materials and Design: The Art and Science of Material Selection in Product Design. Elsevier Butterworth-Heinemann, 2010. 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&#x0D; &#x0D; &#x0D; Introduction&#x0D; &#x0D; In The World Is Not a Desktop, Marc Weisner, the principal scientist and manager of the computer science laboratory at Xerox PARC, stated that, “a good tool is an invisible tool.” Weisner cited eyeglasses as an ideal technology because with spectacles, he argued, “you look at the world, not the eyeglasses.” Although Weisner’s work at PARC played an important role in the creation of the field of “ubiquitous computing”, his ideal is widespread in many areas of technology design. Through repetition, and by design, technologies blend into our lives. While technologies, and communications technologies in particular, have a powerful mediating impact, many of the most pervasive effects are taken for granted by most users. When technology works smoothly, its nature and effects are invisible. But technologies do not always work smoothly. A tiny fracture or a smudge on a lens renders glasses quite visible to the wearer.&#x0D; &#x0D; &#x0D; The Microsoft Windows “Blue Screen of Death” on subway in Seoul (Photo credit Wikimedia Commons).&#x0D; &#x0D; Anyone who has seen a famous “Blue Screen of Death”—the iconic signal of a Microsoft Windows crash—on a public screen or terminal knows how errors can thrust the technical details of previously invisible systems into view. Nobody knows that their ATM runs Windows until the system crashes. Of course, the operating system chosen for a sign or bank machine has important implications for its users. Windows, or an alternative operating system, creates affordances and imposes limitations. Faced with a crashed ATM, a consumer might ask herself if, with its rampant viruses and security holes, she should really trust an ATM running Windows?&#x0D; &#x0D; Technologies make previously impossible actions possible and many actions easier. In the process, they frame and constrain possible actions. They mediate. Communication technologies allow users to communicate in new ways but constrain communication in the process. In a very fundamental way, communication technologies define what their users can say, to whom they say it, and how they can say it—and what, to whom, and how they cannot.&#x0D; &#x0D; Humanities scholars understand the power, importance, and limitations of technology and technological mediation. Weisner hypothesised that, “to understand invisibility the humanities and social sciences are especially valuable, because they specialise in exposing the otherwise invisible.” However, technology activists, like those at the Free Software Foundation (FSF) and the Electronic Frontier Foundation (EFF), understand this power of technology as well. Largely constituted by technical members, both organisations, like humanists studying technology, have struggled to communicate their messages to a less-technical public. Before one can argue for the importance of individual control over who owns technology, as both FSF and EFF do, an audience must first appreciate the power and effect that their technology and its designers have. To understand the power that technology has on its users, users must first see the technology in question. Most users do not.&#x0D; &#x0D; Errors are under-appreciated and under-utilised in their ability to reveal technology around us. By painting a picture of how certain technologies facilitate certain mistakes, one can better show how technology mediates. By revealing errors, scholars and activists can reveal previously invisible technologies and their effects more generally. Errors can reveal technology—and its power and can do so in ways that users of technologies confront daily and understand intimately.&#x0D; &#x0D; The Misprinted Word&#x0D; &#x0D; Catalysed by Elizabeth Eisenstein, the last 35 years of print history scholarship provides both a richly described example of technological change and an analysis of its effects. Unemphasised in discussions of the revolutionary social, economic, and political impact of printing technologies is the fact that, especially in the early days of a major technological change, the artifacts of print are often quite similar to those produced by a new printing technology’s predecessors. From a reader’s purely material perspective, books are books; the press that created the book is invisible or irrelevant. Yet, while the specifics of print technologies are often hidden, they are often exposed by errors.&#x0D; &#x0D; While the shift from a scribal to print culture revolutionised culture, politics, and economics in early modern Europe, it was near-invisible to early readers (Eisenstein). Early printed books were the same books printed in the same way; the early press was conceived as a “mechanical scriptorium.” Shown below, Gutenberg’s black-letter Gothic typeface closely reproduced a scribal hand. Of course, handwriting and type were easily distinguishable; errors and irregularities were inherent in relatively unsteady human hands.&#x0D; &#x0D; &#x0D; Side-by-side comparisons of the hand-copied Malmesbury Bible (left) and the black letter typeface in the Gutenberg Bible (right) (Photo credits Wikimedia Commons &amp; Wikimedia Commons).&#x0D; &#x0D; Printing, of course, introduced its own errors. As pages were produced en masse from a single block of type, so were mistakes. While a scribe would re-read and correct errors as they transcribed a second copy, no printing press would. More revealingly, print opened the door to whole new categories of errors. For example, printers setting type might confuse an inverted n with a u—and many did. Of course, no scribe made this mistake. An inverted u is only confused with an n due to the technological possibility of letter flipping in movable type. As print moved from Monotype and Linotype machines, to computerised typesetting, and eventually to desktop publishing, an accidentally flipped u retreated back into the realm of impossibility (Mergenthaler, Swank).&#x0D; &#x0D; Most readers do not know how their books are printed. The output of letterpresses, Monotypes, and laser printers are carefully designed to produce near-uniform output. To the degree that they succeed, the technologies themselves, and the specific nature of the mediation, becomes invisible to readers. But each technology is revealed in errors like the upside-down u, the output of a mispoured slug of Monotype, or streaks of toner from a laser printer.&#x0D; &#x0D; Changes in printing technologies after the press have also had profound effects. The creation of hot-metal Monotype and Linotype, for example, affected decisions to print and reprint and changed how and when it is done. New mass printing technologies allowed for the printing of works that, for economic reasons, would not have been published before. While personal computers, desktop publishing software, and laser printers make publishing accessible in new ways, it also places real limits on what can be printed. Print runs of a single copy—unheard of before the invention of the type-writer—are commonplace. But computers, like Linotypes, render certain formatting and presentation difficult and impossible.&#x0D; &#x0D; Errors provide a space where the particulars of printing make technologies visible in their products. An inverted u exposes a human typesetter, a letterpress, and a hasty error in judgment. Encoding errors and botched smart quotation marks—a ? in place of a “—are only possible with a computer. Streaks of toner are only produced by malfunctioning laser printers. Dust can reveal the photocopied provenance of a document.&#x0D; &#x0D; Few readers reflect on the power or importance of the particulars of the technologies that produced their books. In part, this is because the technologies are so hidden behind their products. Through errors, these technologies and the power they have on the “what” and “how” of printing are exposed. For scholars and activists attempting to expose exactly this, errors are an under-exploited opportunity.&#x0D; &#x0D; Typing Mistyping&#x0D; &#x0D; While errors have a profound effect on media consumption, their effect is equally important, and perhaps more strongly felt, when they occur during media creation. Like all mediating technologies, input technologies make it easier or more difficult to create certain messages. It is, for example, much easier to write a letter with a keyboard than it is to type a picture. It is much more difficult to write in languages with frequent use of accents on an English language keyboard than it is on a European keyboard. But while input systems like keyboards have a powerful effect on the nature of the messages they produce, they are invisible to recipients of messages. Except when the messages contains errors.&#x0D; &#x0D; Typists are much more likely to confuse letters in close proximity on a keyboard than people writing by hand or setting type. As keyboard layouts switch between countries and languages, new errors appear. The following is from a personal email:&#x0D; &#x0D; hez, if there’s not a subversion server handz, can i at least have the root password for one of our machines? I read through the instructions for setting one up and i think i could do it. [emphasis added]&#x0D; &#x0D; &#x0D; The email was quickly typed and, in two places, confuses the character y with z. Separated by five characters on QWERTY keyboards, these two letters are not easily mistaken or mistyped. However, their positions are swapped on German and English keyboards. In fact, the author was an American typing in a Viennese Internet cafe. The source of his repeated error was his false expectations—his familiarity with one keyboard layout in the context of another. The error revealed the context, both keyboard layouts, and his dependence on a particular keyboard. With the error, the keyboard, previously invisible, was exposed as an inter-mediator with its own particularities and effects.&#x0D; &#x0D; This effect does not change in mobile devices where new input methods have introduced powerful new ways of communicating. SMS messages on mobile phones are constrained in length to 160 characters. The result has been new styles of communication using SMS that some have gone so far as to call a new language or dialect called TXTSPK (Thurlow). Yet while they are obvious to social scientists, the profound effects of text message technologies on communication is unfelt by most users who simply see the messages themselves. More visible is the fact that input from a phone keypad has opened the door to errors which reveal input technology and its effects.&#x0D; &#x0D; In the standard method of SMS input, users press or hold buttons to cycle through the letters associated with numbers on a numeric keyboard (e.g., 2 represents A, B, and C; to produce a single C, a user presses 2 three times). This system makes it easy to confuse characters based on a shared association with a single number. Tegic’s popular T9 software allows users to type in words by pressing the number associated with each letter of each word in quick succession. T9 uses a database to pick the most likely word that maps to that sequence of numbers. While the system allows for quick input of words and phrases on a phone keypad, it also allows for the creation of new types of errors. A user trying to type me might accidentally write of because both words are mapped to the combination of 6 and 3 and because of is a more common word in English. T9 might confuse snow and pony while no human, and no other input method, would.&#x0D; &#x0D; Users composing SMS’s are constrained by its technology and its design. The fact that text messages must be short and the difficult nature of phone-based input methods has led to unique and highly constrained forms of communication like TXTSPK (Sutherland). Yet, while the influence of these input technologies is profound, users are rarely aware of it. Errors provide a situation where the particularities of a technology become visible and an opportunity for users to connect with scholars exposing the effect of technology and activists arguing for increased user control.&#x0D; &#x0D; Google News Denuded&#x0D; &#x0D; As technologies become more complex, they often become more mysterious to their users. While not invisible, users know little about the way that complex technologies work both because they become accustomed to them and because the technological specifics are hidden inside companies, behind web interfaces, within compiled software, and in “black boxes” (Latour). Errors can help reveal these technologies and expose their nature and effects.&#x0D; &#x0D; One such system, Google’s News, aggregates news stories and is designed to make it easy to read multiple stories on the same topic. The system works with “topic clusters” that attempt to group articles covering the same news event. The more items in a news cluster (especially from popular sources) and the closer together they appear in time, the higher confidence Google’s algorithms have in the “importance” of a story and the higher the likelihood that the cluster of stories will be listed on the Google News page. While the decision to include or remove individual sources is made by humans, the act of clustering is left to Google’s software.&#x0D; &#x0D; Because computers cannot “understand” the text of the articles being aggregated, clustering happens less intelligently. We know that clustering is primarily based on comparison of shared text and keywords—especially proper nouns. This process is aided by the widespread use of wire services like the Associated Press and Reuters which provide article text used, at least in part, by large numbers of news sources. Google has been reticent to divulge the implementation details of its clustering engine but users have been able to deduce the description above, and much more, by watching how Google News works and, more importantly, how it fails.&#x0D; &#x0D; For example, we know that Google News looks for shared text and keywords because text that deviates heavily from other articles is not “clustered” appropriately—even if it is extremely similar semantically. In this vein, blogger Philipp Lenssen gives advice to news sites who want to stand out in Google News:&#x0D; &#x0D; Of course, stories don’t have to be exactly the same to be matched—but if they are too different, they’ll also not appear in the same group. If you want to stand out in Google News search results, make your article be original, or else you’ll be collapsed into a cluster where you may or may not appear on the first results page.&#x0D; &#x0D; &#x0D; While a human editor has no trouble understanding that an article using different terms (and different, but equally appropriate, proper nouns) is discussing the same issue, the software behind Google News is more fragile. As a result, Google News fails to connect linked stories that no human editor would miss.&#x0D; &#x0D; &#x0D; A section of a screenshot of Google News clustering aggregation showcasing what appears to be an error.&#x0D; &#x0D; But just as importantly, Google News can connect stories that most human editors will not. Google News’s clustering of two stories by Al Jazeera on how “Iran offers to share nuclear technology,” and by the Guardian on how “Iran threatens to hide nuclear program,” seem at first glance to be a mistake. Hiding and sharing are diametrically opposed and mutually exclusive.&#x0D; &#x0D; But while it is true that most human editors would not cluster these stories, it is less clear that it is, in fact, an error. Investigation shows that the two articles are about the release of a single statement by the government of Iran on the same day. The spin is significant enough, and significantly different, that it could be argued that the aggregation of those stories was incorrect—or not.&#x0D; &#x0D; The error reveals details about the way that Google News works and about its limitations. It reminds readers of Google News of the technological nature of their news’ meditation and gives them a taste of the type of selection—and mis-selection—that goes on out of view. Users of Google News might be prompted to compare the system to other, more human methods. Ultimately it can remind them of the power that Google News (and humans in similar roles) have over our understanding of news and the world around us. These are all familiar arguments to social scientists of technology and echo the arguments of technology activists. By focusing on similar errors, both groups can connect to users less used to thinking in these terms.&#x0D; &#x0D; Conclusion&#x0D; &#x0D; Reflecting on the role of the humanities in a world of increasingly invisible technology for the blog, “Humanities, Arts, Science and Technology Advanced Collaboratory,” Duke English professor Cathy Davidson writes:&#x0D; &#x0D; When technology is accepted, when it becomes invisible, [humanists] really need to be paying attention. This is one reason why the humanities are more important than ever. Analysis—qualitative, deep, interpretive analysis—of social relations, social conditions, in a historical and philosophical perspective is what we do so well. The more technology is part of our lives, the less we think about it, the more we need rigorous humanistic thinking that reminds us that our behaviours are not natural but social, cultural, economic, and with consequences for us all.&#x0D; &#x0D; &#x0D; Davidson concisely points out the strength and importance of the humanities in evaluating technology. She is correct; users of technologies do not frequently analyse the social relations, conditions, and effects of the technology they use. Activists at the EFF and FSF argue that this lack of critical perspective leads to exploitation of users (Stallman). But users, and the technology they use, are only susceptible to this type of analysis when they understand the applicability of these analyses to their technologies. Davidson leaves open the more fundamental question: How will humanists first reveal technology so that they can reveal its effects?&#x0D; &#x0D; Scholars and activists must do more than contextualise and describe technology. They must first render invisible technologies visible. As the revealing nature of errors in printing systems, input systems, and “black box” software systems like Google News show, errors represent a point where invisible technology is already visible to users. As such, these errors, and countless others like them, can be treated as the tip of an iceberg. They represent an important opportunity for humanists and activists to further expose technologies and the beginning of a process that aims to reveal much more.&#x0D; &#x0D; References&#x0D; &#x0D; Davidson, Cathy. “When Technology Is Invisible, Humanists Better Get Busy.” HASTAC. (2007). 1 September 2007 http://www.hastac.org/node/779&gt;. Eisenstein, Elisabeth L. The Printing Press as an Agent of Change: Communications and Cultural Transformations in Early-Modern Europe. Cambridge, UK: Cambridge University Press, 1979. Latour, Bruno. Pandora’s Hope: Essays on the Reality of Science Studies. Harvard UP, 1999. Lenssen, Philipp. “How Google News Indexes.” Google Blogscoped. 2006. 1 September 2007 http://blogoscoped.com/archive/2006-07-28-n49.html&gt;. Mergenthaler, Ottmar. The Biography of Ottmar Mergenthaler, Inventor of the Linotype. New ed. New Castle, Deleware: Oak Knoll Books, 1989. Monotype: A Journal of Composing Room Efficiency. Philadelphia: Lanston Monotype Machine Co, 1913. Stallman, Richard M. Free Software, Free Society: Selected Essays of Richard M. Stallman. Boston, Massachusetts: Free Software Foundation, 2002. Sutherland, John. “Cn u txt?” Guardian Unlimited. London, UK. 2002. Swank, Alvin Garfield, and United Typothetae America. Linotype Mechanism. Chicago, Illinois: Dept. of Education, United Typothetae America, 1926. Thurlow, C. “Generation Txt? The Sociolinguistics of Young People’s Text-Messaging.” Discourse Analysis Online 1.1 (2003). Weiser, Marc. “The World Is Not a Desktop.” ACM Interactions. 1.1 (1994): 7-8.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Citation reference for this article&#x0D; &#x0D; MLA Style&#x0D; Hill, Benjamin Mako. "Revealing Errors." M/C Journal 10.5 (2007). echo date('d M. Y'); ?&gt; &lt;http://journal.media-culture.org.au/0710/01-hill.php&gt;. APA Style&#x0D; Hill, B. (Oct. 2007) "Revealing Errors," M/C Journal, 10(5). Retrieved echo date('d M. Y'); ?&gt; from &lt;http://journal.media-culture.org.au/0710/01-hill.php&gt;. &#x0D;

Introduction Children are not only born digital, they are fashioned toward a lifestyle that needs them to be digital all the time (Palfrey and Gasser). They click, tap, save, circulate, download, and upload the texts of their lives, their friends’ lives, and the anonymous lives of the people that surround them. They are socialised as Internet consumers ready to participate in digital services targeted to them as they age such as Snapchat, Instagram, and YouTube. But they are also fashioned as producers, whereby their lives are sold as content on these same markets. As commodities, the minutiae of their lives become the fodder for online circulation. Paradoxically, we also celebrate these digital behaviours as a means to express identity. Personal profile-building for adults is considered agency-building (Beer and Burrows), and as a consequence, we praise children for mimicking these acts of adult lifestyle. This article reflects on the Kids, Creative Storyworlds, and Wearables project, which involved an ethnographic study with five young children (ages 4-7), who were asked to share their autobiographical stories, creative self-narrations, and predictions about their future mediated lives (Atkins et al.). For this case study, we focus on commercialised forms of children’s automedia, and we compare discussions we had with 6-year old Cayden, a child we met in the study who expresses the desire to make himself famous online, with videos of Jacob, a child vlogger on YouTube’s Kinder Playtime, who clearly influences children like Cayden. We argue that child social influencers need consideration both as autobiographical agents and as child subjects requiring a sheltered approach to their online lives.Automedia Automedia is an emergent genre of autobiography (Smith and Watson Reading 190; “Virtually Me” 78). Broadcasting one’s life online takes many forms (Kennedy “Vulnerability”). Ümit Kennedy argues “Vlogging on YouTube is a contemporary form of autobiography in which individuals engage in a process of documenting their life on a daily or weekly basis and, in doing so, construct[ing] their identity online” (“Exploring”). Sidonie Smith and Julia Watson write that “visual and digital modes are projecting and circulating not just new subjects but new notions of subjectivity through the effects of automediality” with the result that “the archive of the self in time, in space and in relation expands and is fundamentally reorganized” (Reading 190). Emma Maguire addresses what online texts “tell us about cultural understandings of selfhood and what it means to communicate ‘real’ life through media” naming one tool, “automedia”. Further, Julie Rak calls on scholars “to rethink ‘life’ and ‘writing’ as automedia” to further “characterize the enactment of a personal life story in a new media environment.” We define automedia as a genre that involves the practices of creating, performing, sharing, circulating, and (at times) preserving one’s digital life narrative meant for multiple publics. Automedia revises identity formation, embodiment, or corporealities in acts of self-creation (Brophy and Hladki 4). Automedia also emphasizes circulation. As shared digital life texts now circulate through the behaviours of other human subjects, and automatically via algorithms in data assemblages, we contend that automediality currently involves a measure of relinquishing control over perpetually evolving mediatised environments. One cannot control how a shared life narrative will meet a public in the future, which is a revised way of thinking about autobiography. For the sake of this paper, we argue that children’s automedia ought to be considered a creative, autobiographical act, in order to afford child authors who create them the consideration they deserve as agents, now and in the future. Automedial practices often begin when children receive access to a device. The need for a distraction activity is often the reason parents hand a young child a smartphone, iPad, or even a wearable camera (Nansen). Mirroring the lives of parents, children aspire to share representations of their own personal lives in pursuit of social capital. They are often encouraged to use technologies and apps as adults do–to track aspects of self, broadcast life stories and eventually “live share” them—effectively creating, performing, sharing, and at times, seeking to preserve a public life narrative. With this practice, society inculcates children into spheres of device ubiquity, “socializing them to a future digital lifestyle that will involve always carrying a computer in some form” (Atkins et al. 49). Consequently, their representations become inculcated in larger media assemblages. Writing about toddlers, Nansen describes how the “archiving, circulation and reception of these images speaks to larger assemblages of media in which software protocols and algorithms are increasingly embedded in and help to configure everyday life (e.g. Chun; Gillespie), including young children’s media lives (Ito)” (Nansen). Children, like adult citizens, are increasingly faced with choices “not structured by their own preferences but by the economic imperatives of the private corporations that have recently come to dominate the internet” (Andrejevic). Recent studies have shown that for children and youth in the digital age, Internet fame, often characterized by brand endorsements, is a major aspiration (Uhls and Greenfield, 2). However, despite the ambition to participate as celebrity digital selves, children are also mired in the calls to shield them from exposure to screens through institutions that label these activities detrimental. In many countries, digital “protections” are outlined by privacy commissioners and federal or provincial/state statutes, (e.g. Office of the Privacy Commissioner of Canada). Consequently, children are often caught in a paradox that defines them either as literate digital agents able to compose or participate with their online selves, or as subjectified wards caught up in commercial practices that exploit their lives for commercial gain.Kids, Creative Storyworlds and Wearables ProjectBoth academic and popular cultural critics continually discuss the future but rarely directly engage the people who will be empowered (or subjugated) by it as young adults in twenty years. To address children’s lack of agency in these discussions, we launched the Kids, Creative Storyworlds and Wearables project to bring children into a dialogue about their own digital futures. Much has been written on childhood agency and participation in culture and mediated culture from the discipline of sociology (James and James; Jenks; Jenkins). In previous work, we addressed the perspective of child autobiographical feature filmmakers to explore issues of creative agency and consent when adult gatekeepers facilitate children in film production (Pedersen and Aspevig “My Eyes”; Pedersen and Aspevig “Swept”). Drawing on that previous work, this project concentrates on children’s automediated lives and the many unique concerns that materialize with digital identity-building. Children are categorised as a vulnerable demographic group necessitating special policy and legislation, but the lives they project as children will eventually become subsumed in their own adult lives, which will almost certainly be treated and mediated in a much different manner in the future. We focused on this landscape, and sought to query the children on their futures, also considering the issues that arise when adult gatekeepers get involved with child social media influencers. In the Storyworlds ethnographic study, children were given a wearable toy, a Vtech smartwatch called Kidizoom, to use over a month’s timeframe to serve as a focal point for ethnographic conversations. The Kidizoom watch enables children to take photos and videos, which are uploaded to a web interface. Before we gave them the tech, we asked them questions about their lives, including What are machines going to be like in the future? Can you imagine yourself wearing a certain kind of computer? Can you tell/draw a story about that? If you could wear a computer that gave you a super power, what would it be? Can you use your imagination to think of a person in a story who would use technology? In answering, many of them drew autobiographical drawings of technical inventions, and cast themselves in the images. We were particularly struck by the comments made by one participant, Cayden (pseudonym), a 6-year-old boy, and the stories he told us about himself and his aspirations. He expressed the desire to host a YouTube channel about his life, his activities, and the wearable technologies his family already owned (e.g. a GroPro camera) and the one we gave him, the Kidizoom smartwatch. He talked about how he would be proud to publically broadcast his own videos on YouTube, and about the role he had been allowed to play in the making of videos about his life (that were not broadcast). To contextualize Cayden’s commentary and his automedial aspirations, we extended our study to explore child social media influencers who broadcast components of their personal lives for the deliberate purpose of popularity and the financial gain of their parents.We selected the videos of Jacob, a child vlogger because we judged them to be representative of the kinds that Cayden watched. Jacob reviews toys through “unboxing videos,” a genre in which a child tells an online audience her or his personal experiences using new toys in regular, short videos on a social media site. Jacob appears on a YouTube channel called Kinder Playtime, which appears to be a parent-run channel that states that, “We enjoy doing these things while playing with our kids: Jacob, Emily, and Chloe” (see Figure 1). In one particular video, Jacob reviews the Kidizoom watch, serving as a child influencer for the product. By understanding Jacob’s performance as agent-driven automedia, as well as being a commercialised, mediatised form of advertising, we get a clearer picture of how the children in the study are coming to terms with their own digital selfhood and the realisation that circulated, life-exposing videos are the expectation in this context.Children are implicated in a range of ways through “family” influencer and toy unboxing videos, which are emergent entertainment industries (Abidin 1; Nansen and Nicoll; Craig and Cunningham 77). In particular, unboxing videos do impact child viewers, especially when children host them. Jackie Marsh emphasizes the digital literacy practices at play here that co-construct viewers as “cyberflâneur[s]” and she states that “this mode of cultural transmission is a growing feature of online practices for this age group” (369). Her stress, however, is on how the child viewer enjoys “the vicarious pleasure he or she may get from viewing the playing of another child with the toy” (376). Marsh writes that her study subject, a child called “Gareth”, “was not interested in being made visible to EvanHD [a child celebrity social media influencer] or other online peers, but was content to consume” the unboxing videos. The concept of the cyberflâneur, then, is fitting as a mediatising co-constituting process of identity-building within discourses of consumerism. However, in our study, the children, and especially Cayden, also expressed the desire to create, host, and circulate their own videos that broadcast their lives, also demonstrating awareness that videos are valorised in their social circles. Child viewers watch famous children perform consumer-identities to create an aura of influence, but viewers simultaneously aspire to become influencers using automedial performances, in essence, becoming products, themselves. Jacob, Automedial Subjects and Social Media InfluencersJacob is a vlogger on YouTube whose videos can garner millions of views, suggesting that he is also an influencer. In one video, he appears to be around the age of six as he proudly sits with folded hands, bright eyes, and a beaming, but partly toothless smile (see Figure 2). He says, “Welcome to Kinder Playtime! Today we have the Kidi Zoom Smartwatch DX. It’s from VTech” (Kinder Playtime). We see the Kidi Zoom unboxed and then depicted in stylized animations amid snippets of Jacob’s smiling face. The voice and hands of a faceless parent guide Jacob as he uses his new wearable toy. We listen to both parent and child describe numerous features for recording and enhancing the wearer’s daily habits (e.g. calculator, calendar, fitness games), and his dad tells him it has a pedometer “which tracks your steps” (Kinder Playtime). But the watch is also used by Jacob to mediate himself and his world. We see that Jacob takes pictures of himself on the tiny watch screen as he acts silly for the camera. He also uses the watch to take personal videos of his mother and sister in his home. The video ends with his father mentioning bedtime, which prompts a “thank you” to VTech for giving him the watch, and a cheerful “Bye!” from Jacob (Kinder Playtime). Figure 1: Screenshot of Kinder Playtime YouTube channel, About page Figure 2: Screenshot of “Jacob,” a child vlogger at Kinder Playtime We chose Jacob for three reasons. First, he is the same age as the children in the Storyworlds study. Second, he reviews the smart watch artifact that we gave to the study children, so there was a common use of automedia technology. Third, Jacob’s parents were involved with his broadcasts, and we wanted to work within the boundaries of parent-sanctioned practices. However, we also felt that his playful approach was a good example of how social media influence overlaps with automediality. Jacob is a labourer trading his public self-representations in exchange for free products and revenue earned through the monetisation of his content on YouTube. It appears that much of what Jacob says is scripted, particularly the promotional statements, like, “Today we have the Kidizoom Smartwatch DX. It’s from VTech. It’s the smartest watch for kids” (Kinder Playtime). Importantly, as an automedial subject Jacob reveals aspects of his self and his identity, in the manner of many child vloggers on public social media sites. His product reviews are contextualised within a commoditised space that provides him a means for the public performance of his self, which, via YouTube, has the potential to reach an enormous audience. YouTube claims to have “over a billion users—almost one-third of all people on the Internet—and every day people watch hundreds of millions of hours on YouTube and generate billions of views” (YouTube). Significantly, he is not only filmed by others, Jacob is also a creative practitioner, as Cayden aspired to become. Jacob uses high-tech toys, in this case, a new wearable technology for self-compositions (the smart watch), to record himself, friends, family or simply the goings-on around him. Strapped to his wrist, the watch toy lets him play at being watched, at being quantified and at recording the life stories of others, or constructing automediated creations for himself, which he may upload to numerous social media sites. This is the start of his online automediated life, which will be increasingly under his ownership as he ages. To greater or lesser degrees, he will later be able to curate, add to, and remediate his body of automedia, including his digital past. Kennedy points out that “people are using YouTube as a transformative tool, and mirror, to document, construct, and present their identity online” (“Exploring”). Her focus is on adult vloggers who consent to their activities. Jacob’s automedia is constructed collaboratively with his parents, and it is unclear how much awareness he has of himself as an automedia creator. However, if we don’t afford Jacob the same consideration as we afford adult autobiographers, that the depiction of his life is his own, we will reduce his identity performance to pure artifice or advertisement. The questions Jacob’s videos raise around agency, consent, and creativity are important here. Sidonie Smith asks “Can there be a free, agentic space; and if so, where in the world can it be found?” (Manifesto 188). How much agency does Jacob have? Is there a liberating aspect in the act of putting personal technology into the hands of a child who can record his life, himself? And finally, how would an adult Jacob feel about his childhood self advertising these products online? Is this really automediality if Jacob does not fully understand what it means to publicly tell a mediated life story?These queries lead to concerns over child social media influence with regard to legal protection, marketing ethics, and user consent. The rise of “fan marketing” presents a nexus of stealth marketing to children by other children. Stealth marketing involves participants, in this case, fans, who do not know they are involved in an advertising scheme. For instance, the popular Minecon Minecraft conference event sessions have pushed their audience to develop the skills to become advocates and advertisers of their products, for example by showing audiences how to build a YouTube channel and sharing tips for growing a community. Targeting children in marketing ploys seems insidious. Marketing analyst Sandy Fleisher describes the value of outsourcing marketing to fan labourers:while Grand Theft Auto spent $120 million on marketing its latest release, Minecraft fans are being taught how to create and market promotional content themselves. One [example] is Minecraft YouTuber, SkydoesMinecraft. His nearly 7 million strong YouTube army, almost as big as Justin Bieber’s, means his daily videos enjoy a lot of views; 1,419,734,267 to be precise. While concerns about meaningful consent that practices like this raise have led some government bodies, and consumer and child protection groups to advocate restrictions for children, other critics have questioned the limits placed on children’s free expression by such restrictions. Tech commentator Larry Magid has written that, “In the interest of protecting children, we sometimes deny them the right to access material and express themselves.” Meghan M. Sweeney notes that “the surge in collaborative web models and the emphasis on interactivity—frequently termed Web 2.0—has meant that children are not merely targets of global media organizations” but have “multiple opportunities to be active, critical, and resistant producers”...and ”may be active agents in the production and dissemination of information” (68). Nevertheless, writes Sweeney, “corporate entities can have restrictive effects on consumers” (68), by for example, limiting imaginative play to the choices offered on a Disney website, or limiting imaginative topics to commercial products (toys, video games etc), as in YouTube review videos. Automedia is an important site from which to consider young children’s online practices in public spheres. Jacob’s performance is indeed meant to influence the choice to buy a toy, but it is also meant to influence others in knowing Jacob as an identity. He means to share and circulate his self. Julie Rak recalls Paul John Eakin’s claims about life-writing that the “process does not even occur at the level of writing, but at the level of living, so that identity formation is the result of narrative-building.” We view Jacob’s performance along these lines. Kinder Playtime offers him a constrained, parent-sanctioned (albeit commercialised) space for role-playing, a practice bound up with identity-formation in the life of most children. To think through the legality of recognising Jacob’s automedial content as his life, Rak is also useful: “In Eakin’s work in particular, we can see evidence of John Locke’s contention that identity is the expression of consciousness which is continuous over time, but that identity is also a product, one’s own property which is a legal entity”. We have argued that children are often caught in the paradox that defines them either as literate digital creators composing and circulating their online selves or as subjectified personas caught up in commercial advertising practices that use their lives for commercial gain. However, through close observation of individual children, one who we met and questioned in our study, Cayden, the other who we met through his mediated, commercialized, and circulated online persona, Jacob, we argue that child social influencers need consideration as autobiographical agents expressing themselves through automediality. As children create, edit, and grow digital traces of their lives and selves, how these texts are framed becomes increasingly important, in part because their future adult selves have such a stake in the matter: they are being formed through automedia. Moreover, these children’s coming of age may bring legal questions about the ownership of their automedial products such as YouTube videos, an enduring legacy they are leaving behind for their adult selves. Crucially, if we reduce identity performances such as unboxing, toy review videos, and other forms of children’s fan marketing to pure advertisement, we cannot afford Jacob and other child influencers the agency that their self representation is legally and artistically their own.ReferencesAbidin, Crystal. “#familygoals: Family Influencers, Calibrated Amateurism, and Justifying Young Digital Labor.” Social Media + Society 3.2 (2017): 1-15.Andrejevic, Mark. “Privacy, Exploitation, and the Digital Enclosure.” Amsterdam Law Forum 1.4 (2009). &lt;http://amsterdamlawforum.org/article/view/94/168&gt;.Atkins, Bridgette, Isabel Pedersen, Shirley Van Nuland, and Samantha Reid. “A Glimpse into the Kids, Creative Storyworlds and Wearables Project: A Work-in-Progress.” ICET 60th World Assembly: Teachers for a Better World: Creating Conditions for Quality Education – Pedagogy, Policy and Professionalism. 2017. 49-60.Beer, David, and Roger Burrows. “Popular Culture, Digital Archives and the New Social Life of Data.” Theory, Culture &amp; Society 30.4 (2013): 47–71.Brophy, Sarah, and Janice Hladki. 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Introduction This article reports on the emerging findings from a study undertaken as part of an international research collaboration (Australia, Belgium, Italy, UK; DP180103922) exploring the benefits and risks of the Internet of Toys (IoToys). IoToys builds upon technological innovations such as smartphone apps that remotely control home-based objects, and wearable technologies that measure sleep patterns and exercise regimes (Holloway and Green). Mascheroni and Holloway summarise the features of IoToys as entities that users can program, with human-toy interactivity, and which have network connectivity. In this discussion we focus on children’s play with a small programmable robot named Cozmo (fig. 1). The robot also has an ‘explorer mode’ in which children can view the world through the eyes of Cozmo, and a camera which can film the robot’s view, accessed through the mobile app. Children are encouraged to personify Cozmo, including feeding the robot and keeping it tuned up. Cozmo also has numerous functions including tricks, a coding lab, and games that utilise three provided ‘Power Cubes’ that encourage child-robot interaction: Keep Away – the player slides the cube closer to Cozmo then pulls away quickly when Cozmo ‘pounces’ – the aim of the game is to ensure Cozmo misses the cube. Quick Tap – a colour matching game which involves hitting the cubes (before Cozmo) when the colours match. Memory Match – Cozmo shows a pattern of colours, and the player then taps the cubes in the right colour order – each round the pattern gets longer. Fig. 1: Cozmo Whilst the toy uses Wi-Fi rather than connecting directly to the Internet, Cozmo was chosen as a focus for the study because many of its characteristics are typical of IoToys, including connectivity, programmability, and the human-toy connection (Mascheroni and Holloway). Children’s play lives have been changed through the development of digital technologies including smartphones, tablets, laptops, and games consoles (Marsh et al.) and inevitably, children’s play experiences now cross a range of boundaries including the “virtual/physical world, online/offline and digital/nondigital” (Marsh 5). As IoToys become more prevalent in the toy market, there is an increasing need to understand how these connected toys transcend digital-material boundaries between toy and media technology. Whilst toys such as Cozmo share similar traits with traditional toys, they also increasingly share characteristics with computing devices (i.e., video games, mobile apps) and domestic media (i.e., Amazon Alexa; Berriman and Mascheroni). The combination of the traditional and digital adds a layer of complexity to children’s play experiences as the interaction between the child and the robot is ‘reconfigured as a bidirectional, multidimensional, multisensory experience’ (Mascheroni and Holloway 5). By asking ‘what types of play does an Internet-enabled toy engender?’, this article examines the capabilities and limitations of Cozmo for children’s play experiences. Currently, there is little reliable information about children’s IoToy use despite the media attention the subject attracts. Many assumptions are made regarding how technological devices offer restricted opportunities for play (see Healey et al.), and therefore it is vital to investigate the benefits and limitations of these new-generation technologies for parents and children. This article contributes to ongoing debates focussing on children’s playful engagement with digital technology and the importance of engaging parents in discussions on different types of play and children’s development. Methodology This international study involved thirteen families across four countries (Australia, Belgium, Italy, UK; Appendix 1). Ethical clearance was obtained prior to the commencement of the study. Consent was gained from both the children and the parents, and the children were specifically asked if they could be audio-recorded and photographed by the researchers. Pseudonyms have been used in this article. Families were visited twice by a researcher, with each visit lasting around an hour. Firstly, the children were interviewed about their favourite toys, and the parent was interviewed about their thoughts on their children’s (digital) play practices. This provided background information about the child’s play ecologies, such as the extent to which they were familiar with IoToys. Cozmo was also introduced to the children during the first visit and researchers ensured they were confident using the toy before leaving. Cozmo was left with the children to use for a period of between one and three months before the researcher returned for the second visit. Families were reinterviewed, with a focus on what they thought about Cozmo, and how the children had engaged with the toy in their play. Data were deductively analysed using a revised version of Hughes’s taxonomy of play that takes account of the digital aspect of children’s play contexts. Hughes’s original framework, identifying the types of play children engage in, was developed before the rise of digital media. The revised taxonomy was developed by Marsh et al. (see Appendix 2) in a study that examined how apps can promote children’s play and creativity. Data emerging from this study illuminated how Hughes’s taxonomy can be applied in digital contexts, demonstrating that “what changes in digital contexts is not so much the types of play possible, but the nature of that play” (Marsh et al. 250). The adapted framework was applied to the data as a way of analysing play with Cozmo across digital and non-digital spaces, and selections from the transcripts were chosen to illustrate the categories, discussed in the next section. Framing Children’s Digital and Non-Digital Play Practices The findings from the data highlight numerous digital play types (Marsh et al.) that occurred during the children’s interactions with the robot, primarily: Imaginative play in a digital context in which children pretend that things are otherwise. Exploratory play in a digital context in which children explore objects and spaces through the senses to find out information or explore possibilities. Mastery play in digital contexts in which children attempt to gain control of environments. Communication play using words, songs, rhymes, poetry in a digital context. Other types of play that were observed include: Virtual Locomotor play involving movement in a digital context e.g., child may play hide and seek with others in a virtual world. Object play in which children explore virtual objects through vision and touch. Social play in a digital context during which rules for social interaction are constructed and employed. Imaginative Play “Imaginative play” was prevalent in all the case study families, in particular anthropomorphic/zoomorphic play. Anthropomorphic/zoomorphic play can be categorised as imaginative play when children are aware that the object is not real; they display a willing suspension of disbelief. The morphology of social robots is often classified into anthropomorphic (i.e., human-like) and zoomorphic (i.e., animal-like) and different morphologies can elicit differences in how users perceive and interact with robots (Barco et al.). This was the case for the children in this research, who all referred to the fact that the toy was a robot but often described Cozmo as having human/animal attributes. Across the sample, the children talked about Cozmo as if it was a fellow human being or pet. Eleanor (aged 8) stated that “I feel like he’s one of my family”, while Emma (aged 8) said “we sometimes call him ‘brother’ because he is a little bit like family”. Martina (aged 8) observed that Cozmo sometimes has “hiccups'' that prevent him from responding to her queries, reasoning that “it happens by itself because it eats too much”. Louis (aged 9) did not refer to Cozmo as being human, although he did attribute emotions to the toy, mentioning that Cozmo runs in circles whenever he is happy. Sofia’s mother stated that “one thing that made me laugh is that for Sofia it is a puppy. So, she would pet it, give it kisses”. The mother of Aryana (aged 9) commented that “they tried to like treat it like a living thing, not like toy, like a pet . ... They treat it not like something dead or something frozen, something live”. Epley et al. suggest that anthropomorphisation occurs because knowledge that individuals have about humans is developed earlier than knowledge about non-human entities. Therefore, the knowledge children have of being human is drawn upon when encountering objects such as robots. It may be of little surprise that children react like this because, as Marsh (Uncanny Valley 58) argues, “younger children are likely to possess less knowledge about both human and non-human entities than older children and adults, and, therefore, are more likely to anthropomorphise”. Severson and Woodard (2) argue that even in cases where children know the object is not real, the children ascribe feelings, thoughts, and desires to objects in such a serious manner that anthropomorphism is a “pervasive phenomenon that goes beyond mere pretense”. Robot toys such as Cozmo are specifically designed to stimulate anthropomorphism/zoomorphism. Beck et al. have shown that head movements help children identify emotions in robots. Cozmo is programmed to recognise faces and learn names, which inevitably contributes to children feeling an emotional connection. For example, Eleanor (aged 8) remarked that “he was always looking at me and it looked like he was listening to me when I was talking”. The desire for a connection with the robot was so strong for Oscar (aged 7) that he deliberately programmed the robot to respond to him, saying “I can make him do happy stuff which makes me feel like he likes me”. Emma’s mother stated that whenever Emma (aged 8) did something that seemed to make Cozmo happy, she would do those things repeatedly. Emma also referred to Cozmo as having agency, for example, when Cozmo built towers or turned himself into a bulldozer. Even though she made those commands herself via the app, Emma attributed the idea and action to Cozmo. Overall, the children implemented imaginative play practices through the pretence of Cozmo’s ‘human-like’ attributes such as knowing their name, “looking at” and “listening to” them, and displaying different emotions such as love, anger, and happiness. Exploratory Play “Exploratory play” usually occurred when the children first received the toy and most of the children immediately wanted to get to know Cozmo’s features and possibilities. Arthur’s father stated that the first thing Arthur (aged 8) did was grab the remote and start clicking buttons to find out what would happen. Oscar’s mother was amazed that her child had played initially for five hours using Cozmo when he did not spend this long with other toys. She explained that he had been exploring what the toy could do: “he was getting it to choose blocks, pick up blocks, do tricks, make faces, and do dances … . He really enjoyed that”. Controlling Cozmo to travel between rooms was an example of “Virtual Locomotor play”, although the robot could also lead to locomotor play in the physical world as children chased after Cozmo or danced with it. Further examples of virtual locomotor play occurred when the robot followed and chased children if they moved from the play area. Oscar (aged 7) enjoyed using this mode to set the robot on a course which led to it ‘spying’ on his younger sister. His mother noted that: because their bedrooms are opposite sides of the hallway, he kept sending Cozmo to go and watch what she was doing and waiting and seeing how long it took her to realise he was there. Jacob (aged 10) also swiftly realised Cozmo’s surveillance potential as he referred to the robot as a “spying machine”. Louis (aged 9) stated that after he had explored all the options Cozmo offers, playing with it became dull. To him, all the fun was in the exploratory play. Other children across the sample also reported that they stopped playing with Cozmo after a while when they felt like there was nothing new to explore. Mastery Play “Exploratory play” was also connected to “Mastery play” through programmatic sequencing which enabled the robot to move and follow different directions as requested by the children. For example, Eleanor (aged 8) commented, “I liked to play games with him ... . I liked doing the acting thing”. This involved programming the toy to undertake a series of actions that were sequenced in a performance. For Ebrahim (aged 7), the explorer mode also led to mastery play, as he set up an obstacle course for Cozmo using his toy soldiers, explaining that “I took a couple of my soldiers in here and made them out in a specific order and then I tried to get past them in explorer mode”. Arthur (aged 8) would continuously try to find ways to make Cozmo go through obstacle courses faster. He especially liked the coding and programming aspect of the toy, and his father would challenge him to think his decisions through to get better results. Children also utilised other objects in their exploratory and mastery play. Louis (aged 9) would put up barricades so that Cozmo could not escape, and Matteo (aged 9) constructed “high towers” and operated “stability tests” by using Cozmo’s explorer mode and constructing pathways through furniture and other objects. The blurring of physical/virtual and material/digital play, which is prevalent in contemporary play landscapes (Marsh et al., Children, Technology and Play), is highlighted during these episodes in which the children incorporated their own interests linked to their personal environments into their play with Cozmo. Mastery play inevitably involved “Object play”, as children played around with icons on the app to investigate their properties. Cozmo offers a variety of games which stimulate various abilities and can be played via the app or remote. Available games allow both child-robot interaction by means of the ‘Power Cubes’ provided with the robot, and programming games with different difficulty levels. Physical contact between the child and Cozmo, and the robot’s responses, encouraged anthropomorphism, as Jacob (aged 10) switched from referencing Cozmo as ‘it’ to ‘him’ as the discussion progressed: Interviewer: (to Jacob) We got a robot interfacing this time. (To Cozmo) Hello, are you still looking at me? That’s great. (To Jacob) So, do you want to show us your fist bumps that you coded? Jacob: Oh, I didn’t code it. Well, I did code it. Go to tricks. Do you want to fist bump him? Interviewer: Yeah, can I fist bump him? Jacob: Just put your fist near him like close, close, like that. In addition to the fist bump game, Dylan (aged 9) unlocked the Fist Bump app icon on his tablet enabling him to receive rewards by alternating physical fist bumps with himself and virtual fist bumps between Cozmo and the iPad. These object and exploratory play types were positioned as stimulating the robot’s feelings and emotions through musical sounds (like a robot “purring”) that seem to be designed to foster a stronger connection between the child and Cozmo. All the children in the research played Cozmo’s games; the tapping game and the building games with blocks were popular. A clear connection between mastery and object play is shown in those situations where children explore objects to gain control of their environment. While children pointed out that winning the games against Cozmo was almost impossible, some tried to change the game in their favour. Arthur (aged 8), for example, would move the blocks during games to slow down Cozmo. Whenever Emma (aged 8) became impatient with the games, she would move the blocks closer to Cozmo to finish certain games faster. Mastery play was valued by parents because of its interactivity and educational potential. Arthur’s father praised Cozmo’s programming and coding possibilities and valued the technical insight and problem-solving skills it teaches children. Oscar’s mother also valued the educational potential of the toy, but did not appear to recognise that the exploratory play he engaged in involved learning: I liked the fact that it had all these sorts of educational aspects to it. It would have been nice if we’d have got to use them. I like the idea that it could code, and it would teach coding ... but it wasn’t to be. There was some disappointment with the lack of engagement with the coding capabilities of Cozmo. Parents lamented that their children did not engage with coding activities but accepted that this was due to the level of difficulty or technical issues (i.e., Cozmo shutting down frequently), as well as their children’s inability to navigate coding activities (i.e., due to their age). Communication Play “Communication play” was observed as the English-speaking children learnt how to write things into Cozmo that the robot would then say. Ebrahim (aged 7) explained “you can type whatever you want him to say, like, I typed this, ‘I play with Monica’”. Emma (aged 8) made up entire stories for Cozmo to tell, and Arthur (aged 8) made up plays for Cozmo to perform. Oscar (aged 7) felt that the app had helped him learn to read: when asked how it helped him to read, he said “by me typing it in and him saying the words back to me so then I can hear what it says”. This highlights how IoToys can facilitate a playful approach to literacy and supports the work of Heljakka and Ihamäki (96), who assert a need to “widen understandings of toy literacy into multiple directions”. As such, the potential to support aspects of children’s literacy and digital learning in a way that is engaging and playful illuminates the benefits that these types of toys can provide. In contrast, Italian and Belgian children faced more difficulties in communicating with Cozmo as they did not speak English. However, this did not limit the possibility to interact and communicate with Cozmo, for example, through parental mediation or by referring to recognisable symbols (sounds, icons, and images in the app). Other Types of Play The data indicated that four play types (imaginative, exploratory, mastery, and communication play) were the most prevalent among the participating families, although there was also evidence of “Locomotor play” (during exploratory play), and “Object play” (during mastery play). “Social play” was also reported, for instance, when children played with the robot with siblings or friends. All the children wanted to show Cozmo to friends and family. Arthur (aged 8) even arranged with his teacher that he could bring Cozmo to school and show his classmates what Cozmo could do during a class presentation. “Creative play” (play that enables children to explore, develop ideas, and make things in a digital context) was limited in the data. Whilst there was some evidence of this type of play – for example, Oscar (aged 7) and Matteo (aged 9) built ramps and obstacle courses for Cozmo –, in general, there was limited evidence of children playing in creative ways to produce new artefacts with the robot. This is despite the toy having a creative mode, in which children can use the app to code games and actions for Cozmo. For Eleanor, it seemed that the toy did not foster open-ended play. Her mother noted that Eleanor normally enjoyed creative play, but she appeared to lose interest in the toy after displaying initial enthusiasm: “I don’t think it was creative enough, I think it’s not open-ended enough and that’s why she didn’t play with it, would be my guess”. Oscar (aged 7) also lost interest in the toy after the first few weeks of use, which his mother put down to technical issues: I think if it worked flawlessly every time he’d gone to pick it up then he would have been quite happy ... but after a couple of negative experiences where it wouldn’t load up and it’s very frustrating, maybe it just put him off. Other families also talked about how the battery was quick to drain and slow to charge, which impacted on the nature of the play. Emma’s mother stated that the WiFi settings needed to be changed to play with Cozmo which Emma (aged 8) could not do by herself. Therefore, she was only able to play with Cozmo when her mother was around to help her. According to the parents of Arthur and Emma (both aged 8), Cozmo often showed technical errors and did not perform certain games, which caused some frustration with the children. The mother of Aryana (aged 9) also reported a loss of interest in Cozmo, but not particularly related to technical reasons: “she lost interest all the time, so she didn’t follow the steps to the end, she just play a little bit and she'd say, ‘Oh I'm bored, I want to do something’ … mostly YouTube”. Such hesitant engagement may be due to technical issues but might also be due to the limitations regarding creative play identified in this study. Conclusion This study indicates that the Cozmo robot led to a variety of types of play, and that the adaptation of Hughes’s framework by Marsh et al. offered a useful index for identifying changing practices in children's play. As highlighted, children’s play with Cozmo often transcended the virtual and physical, online and offline, and digital and material, as well as providing a vehicle for learning. This analysis thus challenges the proposition that electronic objects limit children’s imagination and play. Prevalent in the findings was the willingness of children to suspend disbelief and engage in anthropomorphic/zoomorphic play with Cozmo by applying human-like attributes to the toy. Children related to the emotional connection with the robot much more than the technical aspects (i.e., coding), and whilst the children understood the limitations of the robot’s agency, there are studies to suggest that caution should be applied by robot developers to ensure that, as technology advances, children are able to maintain the understanding that robots are different from human beings (van den Berghe et al.). This is of particular importance when existing literature highlights that younger children have a less nuanced understanding of the ‘alive’ status of a robot than older children (Nijssen et al.). Children often incorporated more traditional toys and resources into their play with Cozmo: for instance, the use of toy soldiers and building blocks to create obstacle courses demonstrates the digital-material affordances of children’s play. All the children enjoyed the pre-programmed games that utilised the ‘Power Cubes’, and there was an element of competitiveness for the children who demonstrated an eagerness to ‘beat’ the toy. Importantly, parents reported that the app supported children’s literacy development in a playful way, although this was more beneficial for the children whose first language was English. The potential for children’s literacy development through playful child-robot interaction presents opportunities for further study. One significant limitation of the toy that emerged from the findings was the capacity to encourage children’s creative play. Kahn Jr. et al.'s earlier research showed that children endowed less animation to robot toys than to stuffed animals, as if children believe that toy robots have some agency and do not need assistance. Therefore, it is possible that children are less inclined to play in creative ways because they expect Cozmo to control his own behaviour. The research has implications for work with parents. The parents in this study emphasised the value of mastery play for education, but at times overlooked the worth of other types of play for learning. Engaging parents in discussion of the significance that different types of play have for children’s development could be beneficial not just for their own understanding, but also for the types of play they may then encourage and support. The study also has implications for the future development of IoToys. The producers of Cozmo promote types of play through the activities they support in the app, but a broader range of activities could lead to a wider variety of types of play to include, for example, fantasy or dramatic play. There are also opportunities to promote more creative play by, for example, enabling children to construct new artefacts for the robot toy itself, or providing drawing/painting tools that Cozmo could be programmed to use via the app. Broadening play types by design could be encouraged across the toy industry as a whole but, in relation to the IoToys, the opportunities for these kinds of approaches are exciting, reflecting rapid advances in technology that open up possible new worlds of play. This is the challenge for the next few years of toy development, when the first possibilities of the IoToys have been explored. Acknowledgement This research was funded by ARC Discovery Project award DP180103922 – The Internet of Toys: Benefits and Risks of Connected Toys for Children. The article originated as an initiative of the International Partners: Dr Louise Kay and Professor Jackie Marsh (University of Sheffield, UK), Associate Professor Giovanna Mascheroni (Università Cattolica, Italy), and Professor Bieke Zaman (KU Leuven, Belgium). The Australian Chief Investigators on this grant were Dr Donell Holloway and Professor Lelia Green, Edith Cowan University. Much of this article was written by Research Officers who supported the grant’s Investigators, and all parties gratefully acknowledge the funding provided by the Australian Research Council for this project. References Barco, Alex, et al. “Robot Morphology and Children's Perception of Social Robots: An Exploratory Study.” International Conference on Human-Robot Interaction, 23-26 Mar. 2020, Cambridge. 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Appendix 1: Participants Country Name (Pseudonym) Sex Age Siblings 1 UK Eleanor F 8 2 younger brothers 2 UK Ebrahim M 7 2 older sisters 3 UK Oscar M 7 1 younger sister 4 UK Aryana F 9 2 younger brothers 5 AU Jacob M 10 1 younger brother 6 AU Dylan M 9 2 older brothers 7 Italy Martina F 8 2 younger sisters 8 Italy Anna F 8 1 younger sister 9 Italy Luca M 8 1 older brother 10 Italy Matteo M 9 1 younger sister 11 Belgium Louis M 9 2 younger sisters 12 Belgium Emma F 8 1 younger sister 13 Belgium Arthur M 8 1 younger sister Appendix 2: Play Types Play Type Play Types (Hughes) Digital Play Types (adapted by Marsh et al., "Digital Play") Symbolic play Occurs when an object stands for another object, e.g. a stick becomes a horse Occurs when a virtual object stands for another object, e.g. an avatar’s shoe becomes a wand Rough and tumble play Children are in physical contact during play, but there is no violence Occurs when avatars that represent users in a digital environment touch each other playfully, e.g. bumping each other Socio-dramatic play Enactment of real-life scenarios that are based on personal experiences, e.g. playing house Enactment of real-life scenarios in a digital environment that are based on personal experiences Social play Play during which rules for social interaction are constructed and employed Play in a digital context during which rules for social interaction are constructed and employed Creative play Play that enables children to explore, develop ideas, and make things Play that enables children to explore, develop ideas, and make things in a digital context Communication play Play using words, songs, rhymes, poetry, etc. Play using words, songs, rhymes, poetry, etc., in a digital context, e.g. text messages, multimodal communication Dramatic play Play that dramatises events in which children have not directly participated, e.g. TV shows Play in a digital context that dramatises events in which children have not directly participated, e.g. TV shows. Locomotor play Play which involves movement, e.g. chase, hide and seek Virtual locomotor play involves movement in a digital context, e.g. child may play hide and seek with others in a virtual world Deep play Play in which children encounter risky experiences, or feel as though they have to fight for survival Play in digital contexts in which children encounter risky experiences, or feel as though they have to fight for survival Exploratory play Play in which children explore objects, spaces, etc. through the senses in order to find out information, or explore possibilities Play in a digital context in which children explore objects, spaces, etc., through the senses in order to find out information, or explore possibilities Fantasy play Play in which children can take on roles that would not occur in real life, e.g. be a superhero Play in a digital context in which children can take on roles that would not occur in real life, e.g. be a superhero Imaginative play Play in which children pretend that things are otherwise Play in a digital context in which children pretend that things are otherwise Mastery play Play in which children attempt to gain control of environments, e.g. building dens Play in digital contexts in which children attempt to gain control of environments, e.g. creating a virtual world Object play Play in which children explore objects through touch and vision Play in which children explore virtual objects through vision and touch through the screen or mouse Role play Play in which children might take on a role beyond the personal or domestic roles associated with socio-dramatic play Play in a digital context in which children might take on a role beyond the personal or domestic roles associated with socio-dramatic play Recapitulative play Play in which children might explore history, rituals, and myths, and play in ways that resonate with the activities of our human ancestors (lighting fires, building shelters, and so on) Play in a digital context in which children might explore history, rituals, and myths, and play in ways that resonate with the activities of our human ancestors (lighting fires, building shelters, and so on) Transgressive play Play in which children contest, resist, and/or transgress expected norms, rules, and perceived restrictions in both digital and non-digital contexts.