Journal articles: 'Educational chatbot'

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Palasundram, Kulothunkan, Nurfadhlina Mohd Sharef, Nurul Amelina Nasharuddin, Khairul Azhar Kasmiran, and Azreen Azman. "Sequence to Sequence Model Performance for Education Chatbot." International Journal of Emerging Technologies in Learning (iJET) 14, no. 24 (December 19, 2019): 56. http://dx.doi.org/10.3991/ijet.v14i24.12187.

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Chatbot for education has great potential to complement human educators and education administrators. For example, it can be around the clock tutor to answer and clarify any questions from students who may have missed class. A chatbot can be implemented either by ruled based or artificial intel-ligence based. However, unlike the ruled-based chatbots, artificial intelli-gence based chatbots can learn and become smarter overtime and is more scalable and has become the popular choice for chatbot researchers recently. Recurrent Neural Network based Sequence-to-sequence (Seq2Seq) model is one of the most commonly researched model to implement artificial intelli-gence chatbot and has shown great progress since its introduction in 2014. However, it is still in infancy and has not been applied widely in educational chatbot development. Introduced originally for neural machine translation, the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots. However, in-depth research and analysis of op-timal settings of the various components of Seq2Seq model for natural an-swer generation problem is very limited. Additionally, there has been no ex-periments and analysis conducted to understand how Seq2Seq model handles variations is questions posed to it to generate correct answers. Our experi-ments add to the empirical evaluations on Seq2Seq literature and provides insights to these questions. Additionally, we provide insights on how a cu-rated dataset can be developed and questions designed to train and test the performance of a Seq2Seq based question-answer model.

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Memon, Zojan, Hamideh Aghian, Muhammad Shahzad Sarfraz, Akhtar Hussain Jalbani, Rozita Jamili Oskouei, Khuda Bux Jalbani, and Ghulam Hussain Jalbani. "Framework for Educational Domain-Based Multichatbot Communication System." Scientific Programming 2021 (May 5, 2021): 1–9. http://dx.doi.org/10.1155/2021/5518309.

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Education is an area where innovation moves slowly. In this study, we will propose a framework with a novel approach that will support the development of a multi-interactive chatbot’s system for an educational area using AIML 2.0. The system will facilitate the students for their learning towards an outcome-based education domain. The proposed framework will be composed of a user module which consists of user and user interface, chat agents module which will respond to the user query, chatbot KB which will act as the brain for the chatbot system, and socket system for establishing the communication link. Finally, the proposed system will be evaluated using a confusion matrix. The multichatbot communication system will support text-based dialogues on a limited set of questions related to education. However, the system will be implemented in java. The outcomes of this research will be useful for the education sector where these intelligent systems will help the students in schools, universities, and other training scenarios.

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Dimitriadis, George. "Evolution in Education: Chatbots." Homo Virtualis 3, no. 1 (June 16, 2020): 47. http://dx.doi.org/10.12681/homvir.23456.

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Artificial intelligence (AI) programs that simulate interactive human conversation, known as Chatbots, are one of the ongoing trends in the global market. Companies adopt Chatbots in order to offer better services to their customers. Businesses have realized that they are able to enhance the process of customer engagement and operational efficiency through Chatbot technology. Furthermore, most of us have experienced communication of this form in many aspects of our everyday life. This paper examines how Chatbots have evolved over the years, what the advantages and disadvantages of using them are and tries to explain the rise taking place nowadays. Subsequently, it explores the potential of applying this technology in educational settings. Personalized and adaptive learning seems to be imperative today and Chatbot technology can offer invaluable services towards that direction. Finally, it investigates the possibility of using them as virtual teaching assistants relieving teachers from the burden of repetitive tasks and helping them focus more on providing quality education to their students.

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Katre, Mandeep. "Chatbot for Career Counselling." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 30, 2021): 2543–54. http://dx.doi.org/10.22214/ijraset.2021.36718.

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A chatbot is a computer application that is developed to prevaricate and process conversation between humans and digital devices offering the users an experience as if they are communicating with a person in real life instead of a digital device. With today’s customers expecting immediacy and actualization in their interactions with devices, the addition of chatbots as a communication channel has become critical to growing demand. This paper presents the design of an expert system for educational guidance for students available after SSC & HSC. This project is aimed to implement a web-based chatbot using Rasa NLU and machine learning algorithms that analyze user’s queries and understand the user's messages. The bot is designed to address the queries of the user related to the courses they should opt for and colleges that offer the course. The user just has to query through the bot and based on the inputs taken from the user the chatbot will accordingly predict a suitable course for the user. The system responds by showcasing the predicted course for the user. The user can access the bot without any pre-registration.

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Jung, Hyojung, Jinju Lee, and Chaeyeon Park. "Deriving Design Principles for Educational Chatbots from Empirical Studies on Human–Chatbot Interaction." Journal of Digital Contents Society 21, no. 3 (March 31, 2020): 487–93. http://dx.doi.org/10.9728/dcs.2020.21.3.487.

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Faqih, Muhammad Izzatul, and Mustofa Mustofa. "SIMPLE CHATBOT DEVELOPMENT TO HELP STUDENTS UNDERSTANDING EDUCATIONAL RESEARCH METHODOLOGY." Phenomenon : Jurnal Pendidikan MIPA 10, no. 1 (December 15, 2020): 75. http://dx.doi.org/10.21580/phen.2020.10.1.7129.

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Penelitian ini bertujuan untuk (1) Mengembangkan chatbot sederhana untuk membantu mahasiswa memahami metodologi penelitian pendidikan, (2) Mengetahui kelayakan chatbot sederhana untuk membantu mahasiswa memahami metodologi penelitian pendidikan, (3) Mengetahui respon chatbot sederhana untuk membantu mahasiswa memahami metodologi penelitian pendidikan. Jenis penelitian ini adalah penelitian Research and Developement (RND). Teknik pengumpulan data menggunakan observasi, angket, dan dokumentasi. Hasil penelitian aplikasi tersebut layak digunakan yaitu ditandai dengan skor 4,425 yang diberikan oleh 4 ahli teknologi. Pada penilaian SUS aplikasi secara adjective rating bernilai excellent, dengan grade scale bekategori B dan acceptability ranges masuk pada acceptableKata kunci: chatbot, metodologi penelitian pendidikan

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Zahour, Omar. "Towards a Chatbot for educational and vocational guidance in Morocco: Chatbot E-Orientation." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 2 (April 25, 2020): 2479–87. http://dx.doi.org/10.30534/ijatcse/2020/237922020.

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Kadeeva, O. E., and V. N. Syritsyna. "Chatbots and features of their use in education." Informatics in school, no. 10 (December 18, 2020): 45–53. http://dx.doi.org/10.32517/2221-1993-2020-19-10-45-53.

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It's the fact that for decades there has been a search for a system that can imitate human mentors and automate some of their tasks. In the 1980s, intellectual tutoring systems appeared. These are systems that include artificial intelligence and support the student's learning process by offering him expert guidance. However, these are systems that are limited to certain areas of knowledge. Unlike intelligent learning systems, chatbots focus on conversation. Their goal is to achieve interaction in the same patterns as in humans. To maintain conversation, these bots must be able to analyze the environment and offer solutions to problems, interpret emotions of the interlocutor and act accordingly, and also help in learning process. The practical significance of the research presented in the article is that it analyzes the basics of chatbot technology, based on educational needs. Assessment of readiness of chatbot technology for operation at a given moment of time and with modern technological development is given.

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Kharlamenko, I. V., and V. V. Vonog. "Feedback as a form of control in a technogenic educational environment." Informatics and education, no. 5 (July 4, 2020): 44–49. http://dx.doi.org/10.32517/0234-0453-2020-35-5-44-49.

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The article is devoted to control and feedback in foreign language teaching in a technogenic environment. The educational process is transformed in terms of the implementation and active use of digital technologies. ICT-rich environment provides new models of interaction between the teacher, students and digital tools. It also enriches the diversity of tasks and expands the range of possible forms of control and feedback. According to the authors, automated evaluation takes place both in out-of-classroom activities and directly in the classroom using Bring Your Own Device technology (BYOD). Automated control contributes to the intensity of the educational process. It provides all the participants with an opportunity to choose a convenient mode of work and get instant feedback, thereby allowing self-assessment and self-reflection of their own actions. When teaching foreign languages, special attention should be paid to chatbot technology. Chatbots imitate human actions and are able to perform standard repetitive tasks. The growing popularity of bots is explained by a wide range of usage spheres and the ability to integrate chatbots into social networks and mobile technologies. In the technogenic educational environment, ICT can be the basis for interaction, co-editing and peer assessment in collaborative projects. In this case, students receive feedback not only from the teacher, but also from other students, which increases the motivation for independent learning. Thus, automated control, self-assessment and peer assessment can both identify problem areas for each student and design an individual learning path, which increases the effectiveness of learning a foreign language.

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Croes, Emmelyn A. J., and Marjolijn L. Antheunis. "Can we be friends with Mitsuku? A longitudinal study on the process of relationship formation between humans and a social chatbot." Journal of Social and Personal Relationships 38, no. 1 (September 25, 2020): 279–300. http://dx.doi.org/10.1177/0265407520959463.

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This explorative study investigated (a) whether social attraction, self-disclosure, interaction quality, intimacy, empathy and communicative competence play a role in getting-acquainted interactions between humans and a chatbot, and (b) whether humans can build a relationship with a chatbot. Although human-machine communication research suggests that humans can develop feelings for computers, this does not automatically imply that humans experience feelings of friendship with a chatbot. In this longitudinal study, 118 participants had seven interactions with chatbot Mitsuku over a 3-week period. After each interaction participants filled out a questionnaire. The results showed that the social processes decreased after each interaction and feelings of friendship were low. In line with the ABCDE model of relationship development, the social processes that aid relationship continuation decrease, leading to deterioration of the relationship. Furthermore, a novelty effect was at play after the first interaction, after which the chatbot became predictable and the interactions less enjoyable.

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Duran, Miquel, Silvia Simon, and Fernando Blasco. "Science Education and Artificial Intelligence – A Chatbot on Magic and Quantum Computing as an Educational Tool." EDEN Conference Proceedings, no. 1 (June 22, 2020): 137–42. http://dx.doi.org/10.38069/edenconf-2020-ac0011.

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Artificial Intelligence (AI) has entered the realm of higher education and has become an impressive emerging field. Since AI is starting also to be applied to Science Education, here an assay is provided while the opportunities of AI in a particular case of Science Education are reviewed and assessed, namely a chatbot on Quantum Computing, another awesome emerging field. Indeed, Quantum Computing is based on a set of principles that are difficult to understand by the general population, so the ultimate goal of such a chatbot is to learn a few complex concepts in this field and to increase public understanding and awareness of Science. Actually, AI is starting also to be applied to Science Communication, even though progress is not so advanced as in learning.Magic tricks based on mathematical principles are especially well suited to teach difficult concepts, like those related to Quantum Science. They are used to explain entanglement, quantum cryptography, the superposition principle, and other quantum-related concepts – along with other physical and chemical core elements like Entropy.Developing a chatbot is not especially difficult (e.g., with Botpress, Watson, Dialogflow, Manybot, etc.). One may build either scripted, intelligent, or application bots. Indeed, the first ones are those that are easiest to create, and correspond to the first phase of the current project. Intelligent bots understand natural spoken language and correspond to a second phase in this project. In general, Bots are connected to a real-world messaging service, like Facebook Messenger, Twitter, Telegram, Slack, etc.

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Mathew, Ann Neethu, Rohini V., and Joy Paulose. "NLP-based personal learning assistant for school education." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (October 1, 2021): 4522. http://dx.doi.org/10.11591/ijece.v11i5.pp4522-4530.

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Computer-based knowledge and computation systems are becoming major sources of leverage for multiple industry segments. Hence, educational systems and learning processes across the world are on the cusp of a major digital transformation. This paper seeks to explore the concept of an artificial intelligence and natural language processing (NLP) based intelligent tutoring system (ITS) in the context of computer education in primary and secondary schools. One of the components of an ITS is a learning assistant, which can enable students to seek assistance as and when they need, wherever they are. As part of this research, a pilot prototype chatbot was developed, to serve as a learning assistant for the subject Scratch (Scratch is a graphical utility used to teach school children the concepts of programming). By the use of an open source natural language understanding (NLU) or NLP library, and a slackbased UI, student queries were input to the chatbot, to get the sought explanation as the answer. Through a two-stage testing process, the chatbot’s NLP extraction and information retrieval performance were evaluated. The testing results showed that the ontology modelling for such a learning assistant was done relatively accurately, and shows its potential to be pursued as a cloud-based solution in future.

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Samchynska, Yaroslava, Michael Sherman, and Mariya Sikelinda. "IMPLEMENTATION OF THE TOPIC ON CHAT-BOT DEVELOPMENT INTO "OFFICE COMPUTER TECHNOLOGIES" UNIVERSITY COURSE." OPEN EDUCATIONAL E-ENVIRONMENT OF MODERN UNIVERSITY, no. 9 (2020): 121–33. http://dx.doi.org/10.28925/2414-0325.2020.9.10.

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The advisability of modifying the content of “Office Computer Technologies” discipline is reflected in this article by introducing “Development of chatbots with the help of free online development frameworks” topic implementation. The choice of this educational topic is due to the fact that a chatbot is one of the most promising information and communication tools to improve the efficiency of companies. The use of chatbots is one of the most relevant modern ways of communicating with users of mobile devices, which allows companies to reduce marketing costs and the cost of promoting their products and services. The implementation of chatbots can significantly speed up the process of interaction with customers; knowledge and skills in this technology are currently a popular competence for IT professionals in the business environment. The result of studying this topic while studying “Office Computer Technologies” discipline by students is the development of a bot-consultant to work in the Telegram platform, which provides brief information and answers to the company's activities. The implementation of “Development of chatbots with the help of free online development frameworks” topic to the content of “Office Computer Technologies” discipline corresponds to the main focus of educational programs of “Software Engineering”, “Computer Science” and “Information systems and technologies” of the first (bachelor) level of education. The experience of working with students of Kherson State University to study “Development of chatbots with free online resources” topic and the results of the pedagogical experiment showed that it can be successfully implemented into “Office Computer Technology” training course for bachelors - 121 “Software Engineering”, 122 “Computer Science”, 126 “Information Systems and Technologies”, as well as students of related specialties in order to motivate them to solve professional problems and to form research competences.

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Murhadi, Murhadi. "Rancang Bangun Aplikasi Chatbot Sebagai Bentuk Pelayanan Prima Untuk Penerimaan Mahasiswa Baru." INTEK : Jurnal Informatika dan Teknologi Informasi 2, no. 1 (May 30, 2019): 10–16. http://dx.doi.org/10.37729/intek.v2i1.84.

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Excellent service is the best form of service to consumers to feel satisfied. The purpose of excellent service is that consumers or prospective consumers feel underserved and in terms of agencies or companies will increase consumer confidence. Muhammadiyah University Purworejo (UMP) as an educational institution has prospective consumers, namely the millennial generation. The habit of the millennial generation in accessing information is by digitally searching. To access more detailed information, they are accustomed to asking through the texting method via chat. Therefore, the University needs to provide a texting application that can answer questions anytime and with a short reply time.The chat application developed in the form of chatbots.The chat-bot application development begins with studying general questions that are often asked by prospective students. The combination of question words and keywords from each question. From the keywords that are prepared an automatic answer that contains information that the prospective student wants to access. In addition, in each answer a key for information related information will be provided. The results of the design and development of the Chatbot application, namely the implementation of Chatbot can be used as a substitute for the role of humans in providing excellent service. This chatbot can provide quick and complete answers. In terms of the excellent service factor, this Chatbot can fulfill the attitude, attention, action, ability and accountability factors.

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Zahour, Omar, El Habib Benlahmar, Ahmed Eddaoui, Hafsa Ouchra, and Oumaima Hourrane. "A system for educational and vocational guidance in Morocco: Chatbot E-Orientation." Procedia Computer Science 175 (2020): 554–59. http://dx.doi.org/10.1016/j.procs.2020.07.079.

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Bos, Andreia Solange, Michelle Câmara Pizzato, Marcelo Vettori, Lucília Gomes Donato, Paula Poli Soares, James Gladstone Fagundes, and Milton Antônio Zaro. "Empirical Evidence during the Implementation of an Educational Chatbot with the Electroencephalogram Metric." Creative Education 11, no. 11 (2020): 2337–45. http://dx.doi.org/10.4236/ce.2020.1111171.

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Toquero, Cathy Mae Dabi. "‘Sana All’ Inclusive Education amid COVID-19: Challenges, Strategies, and Prospects of Special Education Teachers." International and Multidisciplinary Journal of Social Sciences 10, no. 1 (March 30, 2021): 30–51. http://dx.doi.org/10.17583/rimcis.2020.6316.

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People with Special Educational Needs and Disabilities (SEND) are confronted with diverse challenges as COVID-19 caused tremendous disruption in face-to-face educational settings. Apart from this situation, teachers are also facing difficulties in making their lessons adaptive and responsive to the educational learning needs of people with SEND. This article explores the challenges, strategies, and prospects of teachers for inclusive education during the pandemic. Using a qualitative approach, the researcher gathered data through Messenger chatbot and emails with five special education teachers in the Philippines. Findings revealed that the teachers’ experience educational apprehensions, intermittent virtual socialization, and psychological crisis. However, the teachers assisted the parents in supervising their children with disabilities' through online communication, homeschooling, parental engagement, psychological safety, and empathetic language strategies. The special education teachers also look forward to inclusivity in school policies and government-driven emergency interventions for people with developmental disabilities.

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SEO, Beom-Seok, Tae-Hyeong KIM, and Eung-Kyo SUH. "A study on the construction of artificial intelligence-based chatbot and the acceptance intention in educational service." KODISA International Conference on Business and Economics (KODISA.ICBE) 2019, no. 7 (July 8, 2019): 475–78. http://dx.doi.org/10.35646/kodisa.icbe.2019.7.5.475.

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Coniam, David. "Evaluating the language resources of chatbots for their potential in English as a second language." ReCALL 20, no. 1 (January 2008): 98–116. http://dx.doi.org/10.1017/s0958344008000815.

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AbstractThis paper investigates the linguistic worth of current ‘chatbot’ programs – software programs which attempt to hold a conversation, or interact, in English – as a precursor to their potential as an ESL (English as a second language) learning resource. After some initial background to the development of chatbots, and a discussion of the Loebner Prize Contest for the most ‘human’ chatbot (the ‘Turing Test’), the paper describes an in-depth study evaluating the linguistic accuracy of a number of chatbots available online. Since the ultimate purpose of the current study concerns chatbots' potential with ESL learners, the analysis of language embraces not only an examination of features of language from a native-speaker's perspective (the focus of the Turing Test), but also aspects of language from a second-language-user's perspective. Analyses indicate that while the winner of the 2005 Loebner Prize is the most able chatbot linguistically, it may not necessarily be the chatbot most suited to ESL learners. The paper concludes that while substantial progress has been made in terms of chatbots' language-handling, a robust ESL ‘conversation practice machine’ (Atwell, 1999) is still some way off being a reality.

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Bunge, Eduardo L. "6.1 ARTIFICIAL INTELLIGENCE CHATBOT FOR DEPRESSION IN YOUTH: DEVELOPMENT, USAGE, AND OUTCOMES." Journal of the American Academy of Child & Adolescent Psychiatry 59, no. 10 (October 2020): S274—S275. http://dx.doi.org/10.1016/j.jaac.2020.07.578.

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Mendez, Sylvia, Katie Johanson, Valerie Martin Conley, Kinnis Gosha, Naja A Mack, Comas Haynes, and Rosario A Gerhardt. "Chatbots: A Tool to Supplement the Future Faculty Mentoring of Doctoral Engineering Students." International Journal of Doctoral Studies 15 (2020): 373–92. http://dx.doi.org/10.28945/4579.

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Aim/Purpose: The purpose of this paper is to explore the efficacy of simulated interactive virtual conversations (chatbots) for mentoring underrepresented minority doctoral engineering students who are considering pursuing a career in the professoriate or in industry. Background: Chatbots were developed under the National Science Foundation INCLUDES Design and Developments Launch Pilot award (17-4458) and provide career advice with responses from a pre-programmed database populated by renowned emeriti engineering faculty. Chatbots have been engineered to fulfill a myriad of roles, such as undergraduate student advisement, but no research has been found that addresses their use with supplemental future faculty mentoring for doctoral students. Methodology: Chatbot efficacy is examined through a phenomenological design with focus groups with underrepresented minority doctoral engineering students. No theoretical or conceptual frameworks exist relative to chatbots designed for future faculty mentoring; therefore, an adaptation and implementation of the conceptual model posited on movie recommendations was utilized to ground this study. The four-stage process of phenomenological data analysis was followed: epoché, horizontalization, imaginative variation, and synthesis. Contribution: No studies have investigated the utility of chatbots in providing supplemental mentoring to future faculty. This phenomenological study contributes to this area of investigation and provides greater consideration into the unmet mentoring needs of these students, as well as the potential of utilizing chatbots for supplementary mentoring, particularly for those who lack access to high quality mentoring. Findings: Following the data analysis process, the essence of the findings was, while underrepresented minority doctoral engineering students have ample unmet mentoring needs and overall are satisfied with the user interface and trustworthiness of chatbots, their intent to use them is mixed due to a lack of personalization in this type of supplemental mentoring relationship. Recommendations for Practitioners: One of the major challenges faced by underrepresented doctoral engineering students is securing quality mentoring relationships that socialize them into the engineering culture and community of practice. While creating opportunities for students and incentivizing faculty to engage in the work of mentoring is needed, we must also consider the ways in which to leverage technology to offer supplemental future faculty mentoring virtually. Recommendation for Researchers: Additional research on the efficacy of chatbots in providing career-focused mentoring to future faculty is needed, as well as how to enhance the functionality of chatbots to create personal connections and networking opportunities, which are hallmarks of traditional mentoring relationships. Impact on Society: An understanding of the conceptual pathway that can lead to greater satisfaction with chatbots may serve to expand their use in the realm of mentoring. Scaling virtual faculty mentoring opportunities may be an important breakthrough in meeting mentoring needs across higher education. Future Research: Future chatbot research must focus on connecting chatbot users with human mentors; standardizing the process for response creation through additional data collection with a cadre of diverse, renowned faculty; engaging subject matter experts to conduct quality verification checks on responses; testing new responses with potential users; and launching the chatbots for a broad array of users.

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Deyneko, T. A., O. L. Epanchintseva, and A. V. Rodyukov. "Electronic schedule at the university on the basis of 1C:Automated scheduling. University on the example of Omsk State University." Informatics and education, no. 2 (April 27, 2021): 33–40. http://dx.doi.org/10.32517/0234-0453-2021-36-2-33-40.

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Automating scheduling is a classic task in learning management systems. The process of scheduling is, in a sense, the final one in the chain of support of educational activities, and its automation reveals all inconsistencies and shortcomings of the previous processes. In order for the scheduling to be automated as much as possible, a lot of various initial information should be processed in the information systems of the university — curricula, staff, workload, schedule of the educational process, contingent of students, classroom fund. It is especially difficult for universities with educational programs of various orientations — natural science, humanitarian, creative, etc., which have specific principles for organizing and conducting classes.The level of automation of educational activities at Dostoevsky Omsk State University, a classical university with a wide variety of types of educational programs, made it possible to tackle the task of scheduling. However, during the implementation of the automated scheduling system, the project team faced a number of problems.The article describes the results of the project for the transition to an electronic schedule in Dostoevsky Omsk State University using the circulation software product 1C:Automated scheduling. University based on the 1C:Enterprise 8.3 system. Initial data on the individual workload of teachers, the classroom fund, the list of student groups, and the list of disciplines were loaded into the configuration from the existing information system of design of Dostoevsky Omsk State University. Based on the results of the audit of the downloaded reference information, the initial data, including curricula, were normalized. The compiled schedule in two modes (manual and automatic) was published on the official website of the university and is used to operate a chatbot on the VKontakte network to inform students and teachers about upcoming classes.

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Minati, Gianfranco. "Complex Cognitive Systems and Their Unconscious. Related Inspired Conjectures for Artificial Intelligence." Future Internet 12, no. 12 (November 27, 2020): 213. http://dx.doi.org/10.3390/fi12120213.

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The aim of the article is to propose a conceptual framework, constructs, and conjectures to act as a guide for future, related research finalized to design and implement versions of Artificial Intelligence encompassing an artificially simulated unconscious suitable for human-like artificial cognitive processing. This article considers the concept of the unconscious in psychoanalysis. The interdisciplinary understanding of this concept is considered to be the unavoidable property of sufficiently complex, cognitive processing. We elaborate on the possibility of an artificial unconscious, able to both self-acquired properties through usage, and self-profile through a supposed implicit, parasitic usage of explicit cognitive processing. Memory activities are considered to be integrated into cognitive processing, with memory no longer only being storage and reminding no longer only being finding. We elaborate on the artificial unconscious as an implicit, usage-dependent, self-profiling, and emergent process. Conceptual characteristics of the research project are the implementation of weighted networked, fuzzified memorizations; self-generated networks of links of inter-relationships as nodes, self-variation of the intensity of the links according to the use, and activation of internal self-processes such as the introduction of fictitious links intended as variations and combinations of the current ones. Application examples suitable for experimental implementation are also discussed with reference to chatbot technology that has been extended with features of an artificial unconscious. Thus, we introduce the concept of the AU-chatbot. The main purpose is to allow the artificial cognitive processing to acquire suitable human-like attitudes in representing, interfacing, and learning, potentially important in supporting and complementing human-centered activities. Examples of expected features are the ability to combine current and unconscious links to perform cognitive processing such as representing, deciding, memorizing, and solving equivalencies, and also learning meta-profiles, such as in supporting doctor–patient interactions and educational activities. We also discuss possible technologies suitable for implementing experiments for the artificial unconscious.

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Guillon, Quentin, Sophie Baduel, Mado Arnaud, and Bernadette Rog�. "Nouvelles technologies au service du d�pistage�: Chatbot pour la d�tection pr�coce de l�autisme." Enfance N�1, no. 1 (2019): 59. http://dx.doi.org/10.3917/enf2.191.0059.

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Kazim, Emre, Adriano Soares Koshiyama, Airlie Hilliard, and Roseline Polle. "Systematizing Audit in Algorithmic Recruitment." Journal of Intelligence 9, no. 3 (September 17, 2021): 46. http://dx.doi.org/10.3390/jintelligence9030046.

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Business psychologists study and assess relevant individual differences, such as intelligence and personality, in the context of work. Such studies have informed the development of artificial intelligence systems (AI) designed to measure individual differences. This has been capitalized on by companies who have developed AI-driven recruitment solutions that include aggregation of appropriate candidates (Hiretual), interviewing through a chatbot (Paradox), video interview assessment (MyInterview), and CV-analysis (Textio), as well as estimation of psychometric characteristics through image-(Traitify) and game-based assessments (HireVue) and video interviews (Cammio). However, driven by concern that such high-impact technology must be used responsibly due to the potential for unfair hiring to result from the algorithms used by these tools, there is an active effort towards proving mechanisms of governance for such automation. In this article, we apply a systematic algorithm audit framework in the context of the ethically critical industry of algorithmic recruitment systems, exploring how audit assessments on AI-driven systems can be used to assure that such systems are being responsibly deployed in a fair and well-governed manner. We outline sources of risk for the use of algorithmic hiring tools, suggest the most appropriate opportunities for audits to take place, recommend ways to measure bias in algorithms, and discuss the transparency of algorithms.

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Villanueva Jr., George R. "Design Architecture of FAQ Chatbot for Higher Education Institution." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 189–96. http://dx.doi.org/10.5373/jardcs/v12sp1/20201062.

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Lee, Jang Ho, Hyejin Yang, Dongkwang Shin, and Heyoung Kim. "Chatbots." ELT Journal 74, no. 3 (July 2020): 338–44. http://dx.doi.org/10.1093/elt/ccaa035.

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Abstract In this series, we explore technology-related themes and topics. This series aims to discuss and demystify what may be new areas for some readers and to consider their relevance for English language teachers.

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Cai, William, Josh Grossman, Zhiyuan Jerry Lin, Hao Sheng, Johnny Tian-Zheng Wei, Joseph Jay Williams, and Sharad Goel. "Bandit algorithms to personalize educational chatbots." Machine Learning 110, no. 9 (May 25, 2021): 2389–418. http://dx.doi.org/10.1007/s10994-021-05983-y.

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Vanichvasin, Patchara. "Chatbot Development as a Digital Learning Tool to Increase Students’ Research Knowledge." International Education Studies 14, no. 2 (January 27, 2021): 44. http://dx.doi.org/10.5539/ies.v14n2p44.

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The research aimed to: 1) develop the chatbot; 2) evaluate its effectiveness; and 3) investigate its effects on students’ research knowledge. The sample consisted of 36 Thai university students. The research instruments consisted of: 1) the chatbot; 2) an evaluation form; 3) an effectiveness questionnaire; and 4) research tests. Data analysis used was mean, standard deviation, content analysis and a t-test. The findings indicated that: 1) the chatbot was evaluated by experts with the applicability at a very high level ( = 4.67, S.D. = 0.08) with recommendation to add more research content and interactive learning. The pilot test was done with 14 non-target group of students. Students perceived the chatbot’s effectiveness at a high level ( = 4.43, S.D. = 0.35) with comments to add more examples and graphics to make the chatbot more interesting; 2) the 36 target group of Thai university students perceived the chatbot as an effective technology to use as a digital learning tool at a high level ( = 4.37, S.D. = 0.48). They thought that chatbot technology was easy to use, easy to understand, innovative and fun for learning. They could get answers instantly and be able to seek specific information without waiting for responses. However, in response to questions not matched keywords specified, further details of finding proper answers such as links should be provided instead of leaving those questions unanswered. Also, the chatbot only provided responses when typing correctly so there should be an option to choose from a list of questions or keywords; and 3) the post-test scores were significantly higher than the pre-test scores at the 0.05 level of significance. In conclusion, using chatbot technology in education settings to increase students’ research knowledge gave positive results as it led to positive learning outcomes and helped provide better personalized learning experience for students.

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Smutny, Pavel, and Petra Schreiberova. "Chatbots for learning: A review of educational chatbots for the Facebook Messenger." Computers & Education 151 (July 2020): 103862. http://dx.doi.org/10.1016/j.compedu.2020.103862.

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Chen, Hsiu-Ling, Gracia Vicki Widarso, and Hendri Sutrisno. "A ChatBot for Learning Chinese: Learning Achievement and Technology Acceptance." Journal of Educational Computing Research 58, no. 6 (June 10, 2020): 1161–89. http://dx.doi.org/10.1177/0735633120929622.

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ChatBot has potential as a language learning tool, especially for learning Chinese vocabulary. This study aimed to investigate the impact of using a newly developed ChatBot to learn Chinese vocabulary by comparing how it works in different learning environments and to explore the ChatBot with reference to the Technology Acceptance Model (TAM). This study was conducted with 58 students divided into two independent groups. The control group used ChatBot in a one-on-many classroom. The experimental group applied the ChatBot in one-on-one tutor sessions. A pretest and a posttest were used to measure the effect of the ChatBot, while TAM was explored through questionnaire and interview. Data analysis includes a paired-sample t test, analysis of covariance, and levels of effect. The results indicated that the ChatBot significantly improved the students’ learning achievement and that having a one-on-one environment may lead to better outcome than what could be achieved in a classroom. The TAM model was tested using partial least square. The result showed that perceived usefulness was the predictor of behavioral intention, whereas perceived ease of use was not. The students agreed that the ChatBot benefited their learning of Chinese vocabulary, with several adjustments need to be made for further progress.

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Malik, Reena, Ambuj Shrama, Sonal Trivedi, and Rikkee Mishra. "Adoption of Chatbots for Learning among University Students: Role of Perceived Convenience and Enhanced Performance." International Journal of Emerging Technologies in Learning (iJET) 16, no. 18 (September 20, 2021): 200. http://dx.doi.org/10.3991/ijet.v16i18.24315.

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With the advent of internet and exponentially growing smartphone market, chatbots are becoming popular and are being widely used for interactions in varied fields. This study investigated the usage of chatbots for educational/learning purpose by university students. Wide research has been done exploring usage of chatbots in service industry; still there is vacuum regarding usage of chatbots in education for effective learning. Using path analysis, the study demonstrates validation of two newly added constructs as an extension in Technology Adoption Model and tries to understand the antecedents for intension to adopt chatbots. This study is of utmost importance to researchers, policy makers, system designers for e- learning platforms, teachers, and students in order to make learning effective.

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Panchal, Parth, Janak Thakkar, Veerapathiramoorthy Pillai, and Shweta Patil. "Automatic Question Generation and Evaluation." Journal of University of Shanghai for Science and Technology 23, no. 05 (May 28, 2021): 751–61. http://dx.doi.org/10.51201/jusst/21/05203.

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Generation of questions from an extract is a very tedious task for humans and an even tougher one for machines. In Automatic Question Generation (AQG), it is extremely important to examine the ways in which this can be achieved with sufficient levels of accuracy and efficiency. The way in which this can be taken ahead is by using Natural Language Processing (NLP) to process the input and to work with it for AQG. Using NLP with question generation algorithms the system can generate the questions for a better understanding of the text document. The input is pre-processed before actually moving in for the question generation process. The questions formed are first checked for proper context satisfaction with the context of the input to avoid invalid or unanswerable question generation. It is then preprocessed using various NLP-based mechanisms like tokenization, named entity recognition(NER) tagging, parts of speech(POS) tagging, etc. The question generation system consists of a machine learning classification-based Fill in the blank(FIB) generator that also generates multiple choices and a rule-based approach to generate Wh-type questions. It also consists of a question evaluator where the user can evaluate the generated question. The results of these evaluations can help in improving our system further. Also, evaluation of Wh questions has been done using the BLEU score to determine whether the automatically generated questions resemble closely the human-generated ones. This system can be used in various places to help ease the question generation and also at self-evaluator systems where the students can assess themselves so as to determine their conceptual understanding. Apart from educational use, it would also be helpful in building chatbot-based applications. This work can help improve the overall understanding of the level to which the concept given is understood by the candidate and the ways in which it can be understood more properly. We have taken a simple yet effective approach to generate the questions. Our evaluation results show that our model works well on simpler sentences.

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Skjuve, Marita, Asbjørn Følstad, Knut Inge Fostervold, and Petter Bae Brandtzaeg. "My Chatbot Companion - a Study of Human-Chatbot Relationships." International Journal of Human-Computer Studies 149 (May 2021): 102601. http://dx.doi.org/10.1016/j.ijhcs.2021.102601.

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Vysotskaya, Polina, Svetlana Zabelina, Julia Kuleshova, and Irina Pinchuk. "Using the capabilities of artificial intelligence in the development of reflection skills." E3S Web of Conferences 210 (2020): 22035. http://dx.doi.org/10.1051/e3sconf/202021022035.

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The problems of developing of soft skills of people involved in educational activities are examined, their composition in the field of education is revealed. Special attention is paid to the formation of reflective skills using the capabilities of artificial intelligence, in particular Chatbots. A technique has been developed for implementing the reflective management of the student’s intellectual activity in the Chatbots system. Case scenaries are proposed that immerse the user in the problem space of the educational situation. The effectiveness of using the capabilities of artificial intelligence in the formation of reflective skill is proved.

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Rapp, Amon, Lorenzo Curti, and Arianna Boldi. "The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots." International Journal of Human-Computer Studies 151 (July 2021): 102630. http://dx.doi.org/10.1016/j.ijhcs.2021.102630.

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Maher, Carol Ann, Courtney Rose Davis, Rachel Grace Curtis, Camille Elizabeth Short, and Karen Joy Murphy. "A Physical Activity and Diet Program Delivered by Artificially Intelligent Virtual Health Coach: Proof-of-Concept Study." JMIR mHealth and uHealth 8, no. 7 (July 10, 2020): e17558. http://dx.doi.org/10.2196/17558.

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Background Poor diet and physical inactivity are leading modifiable causes of death and disease. Advances in artificial intelligence technology present tantalizing opportunities for creating virtual health coaches capable of providing personalized support at scale. Objective This proof of concept study aimed to test the feasibility (recruitment and retention) and preliminary efficacy of physical activity and Mediterranean-style dietary intervention (MedLiPal) delivered via artificially intelligent virtual health coach. Methods This 12-week single-arm pre-post study took place in Adelaide, Australia, from March to August 2019. Participants were inactive community-dwelling adults aged 45 to 75 years, recruited through news stories, social media posts, and flyers. The program included access to an artificially intelligent chatbot, Paola, who guided participants through a computer-based individualized introductory session, weekly check-ins, and goal setting, and was available 24/7 to answer questions. Participants used a Garmin Vivofit4 tracker to monitor daily steps, a website with educational materials and recipes, and a printed diet and activity log sheet. Primary outcomes included feasibility (based on recruitment and retention) and preliminary efficacy for changing physical activity and diet. Secondary outcomes were body composition (based on height, weight, and waist circumference) and blood pressure. Results Over 4 weeks, 99 potential participants registered expressions of interest, with 81 of those screened meeting eligibility criteria. Participants completed a mean of 109.8 (95% CI 1.9-217.7) more minutes of physical activity at week 12 compared with baseline. Mediterranean diet scores increased from a mean of 3.8 out of 14 at baseline, to 9.6 at 12 weeks (mean improvement 5.7 points, 95% CI 4.2-7.3). After 12 weeks, participants lost an average 1.3 kg (95% CI –0.1 to –2.5 kg) and 2.1 cm from their waist circumference (95% CI –3.5 to –0.7 cm). There were no significant changes in blood pressure. Feasibility was excellent in terms of recruitment, retention (90% at 12 weeks), and safety (no adverse events). Conclusions An artificially intelligent virtual assistant-led lifestyle-modification intervention was feasible and achieved measurable improvements in physical activity, diet, and body composition at 12 weeks. Future research examining artificially intelligent interventions at scale, and for other health purposes, is warranted.

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A.V., Boichenko, and Boichenko O.A. "Online education empowerment with artificial intelligence tools." Artificial Intelligence 25, no. 2 (July 15, 2020): 22–29. http://dx.doi.org/10.15407/jai2020.02.022.

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The experience of organizing the educational process during the quarantine caused by the COVID-19 pandemic is considered. Using of interactive technologies that allow organizing instant audio communication with a remote audience, as well as intelligent tools based on artificial intelligence that can help educational institutions to work more efficiently. Examples of sufficient use of artificial intelligence in distance learning are given. Particular attention is paid to the development of intelligent chatbots intended for use in communications with students of online courses of educational web portals. The use of technologies of ontology formation based on automatic extraction of concepts from external sources is offered, what can lead to greater acceleration of construction of the intellectual component of chatbots. Artificial intelligence tools can become an essential part of distance learning during this global COVID-19 pandemic. While educational institutions are closed to quarantine and many of them transitioned to distance learning lecturers and schoolteachers, as well as students and schoolchildren faced with the necessity to study in this new reality. The impact of these changes depends on people's ability to learn and on the role that the education system will play in meeting the demand for quality and affordable training. The experience of organizing the educational process at the University of Education Management of the National Academy of Pedagogical Sciences of Ukraine in the quarantine caused by the COVID-19 pandemic showed that higher and postgraduate institutions were mostly ready to move to distance learning. However, most distance learning systems, on whatever platform they are organized, need to be supplemented: the ability to broadcast video (at least ‒ one-way streaming), providing fast transmission of various types of information, receiving instant feedback when voting, polls and more. The structure of each section of the training course for the online learning system should fully cover the training material and meet all the objectives of the course. Appropriate language should be used, and wording, syntax, and presentation of tasks should be considered. One of the areas of application of artificial intelligence technologies in online learning is the use of chatbots which are characterrized by the following properties. It is advisable to use computer ontologies to ensure the intellectualization of chatbots. In this case, the metadata must be understandable to both humans and software and meet the requirements of modern standards in the field of information technology. The extraction of concepts from external data sources was carried out to build the ontology.

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Sarosa, Moechammad, Herman Tolle, Mokhamad Hadi Wijaya, and Amalia Rakhmania. "Chatbot in Online Classes Using Organizing Exercise Items." International Journal of Continuing Engineering Education and Life-Long Learning 30, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijceell.2020.10028915.

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Deveci Topal, Arzu, Canan Dilek Eren, and Aynur Kolburan Geçer. "Chatbot application in a 5th grade science course." Education and Information Technologies 26, no. 5 (June 17, 2021): 6241–65. http://dx.doi.org/10.1007/s10639-021-10627-8.

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Carayannopoulos, Sofy. "Using chatbots to aid transition." International Journal of Information and Learning Technology 35, no. 2 (March 5, 2018): 118–29. http://dx.doi.org/10.1108/ijilt-10-2017-0097.

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Purpose The purpose of this paper is to examine how chatbots can be used to address two key struggles that students face in first year – a sense of being disconnected from the instructor, and information overload. The authors propose that chatbots can be a useful tool for helping students navigate the volumes of information that confront them as they begin attending university, while at the same time feeling somewhat personally connected with the instructor. This is achieved without increasing instructor time commitment, and perhaps reducing it in large classes. The paper reveals the results of applying this tool in a large first year class and proposes improvements for future iterations. Design/methodology/approach A tool was designed and implemented and tested against research insights. Findings Chatbots are an effective means to reduce student transition challenges. Research limitations/implications Technology which feels social and personal as well as functioning on a tool that students use will make the student feel more connected to the course and the instructor. Practical implications Tools aiding transition should be easy to use and allow customizable information access. Originality/value Chatbots are an unexplored tool. They have the benefit of addressing information overload as well as making the student feel socially connected without increasing instructor workload.

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Selamat, Moch Akbar, and Nila Armelia Windasari. "Chatbot for SMEs: Integrating customer and business owner perspectives." Technology in Society 66 (August 2021): 101685. http://dx.doi.org/10.1016/j.techsoc.2021.101685.

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Hrynyayeva, Natalia, and Kateryna Kiriukha. "THE USE OF MODERN ICT IN CLASSROOM WORK IN THE FORMATION OF CIVIC AND PROFESSIONALLY ORIENTED FOREIGN COMPETENCE OF THE FUTURE FUTURE." Academic Notes Series Pedagogical Science 1, no. 192 (March 2021): 170–74. http://dx.doi.org/10.36550/2415-7988-2021-1-192-170-174.

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The article analyzes the use of modern ICT in classroom work in the integration of civic and foreign language competencies. During the study, a set of complementary methods was used, which allowed to analyze the theoretical and methodological developments of domestic and foreign scientists on this method of active training of future specialists in the food industry. The methodology of research work is based on theoretical methods of scientific knowledge. The purpose of the study is to theoretically substantiate and analyze the specifics of the use of modern ICT in classroom work in the formation of civic and professionally oriented foreign language competence of future specialists in the food industry. In the course of the work the specifics of using modern ICT in classroom work in the formation of civic and professionally oriented foreign language competencies of future food industry specialists are considered, and the theoretical and methodological bases of the problem of using modern ICT in classrooms are substantiated. It is noted that the introduction of new innovative technologies, including the SMART Board interactive whiteboard with the involvement of SMART Notebook software, educational chatbots are modern tools that should help achieve this goal. The results showed that ICTs create ample opportunities for the development of modern education and allow to effectively build the learning process. Information and communication technologies (ICT) create ample opportunities for the development of modern education, primarily in the direction of individualization, create conditions for the realization of the creative potential of teachers and students. ICT educational tools include a variety of software and hardware designed to solve certain pedagogical problems that have a substantive content and are focused on interaction with students. In the field of teaching, the technology of using ICT opens up new didactic opportunities associated with the visualization of the material, its «revival”, the ability to visualize those phenomena and processes that cannot be demonstrated in other ways. There is an opportunity to concentrate large amounts of educational material from different sources, presented in different forms, optimally selected and composed by the teacher depending on the needs of students and the characteristics of the program. We consider the interactive whiteboard and the SMART Notebook program to be the most perfect technical tool for classroom work. The use of chatbots is promising and appropriate in the educational process.

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Min, Yunjeung, Jaekyung Ahn, and Soyoung Kim. "Structural Relationship Analysis between the Intention to Use Educational Chatbots and Influential Factors based on Technology Acceptance Model." Korean Association for Educational Information and Media 26, no. 4 (December 31, 2020): 799–825. http://dx.doi.org/10.15833/kafeiam.26.4.799.

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Min, Yunjeung, Jaekyung Ahn, and Soyoung Kim. "Structural Relationship Analysis between the Intention to Use Educational Chatbots and Influential Factors based on Technology Acceptance Model." Korean Association for Educational Information and Media 26, no. 4 (December 31, 2020): 799–825. http://dx.doi.org/10.15833/kafeiam.26.4.799.

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Mokmin, Nur Azlina Mohamed, and Nurul Anwar Ibrahim. "The evaluation of chatbot as a tool for health literacy education among undergraduate students." Education and Information Technologies 26, no. 5 (May 25, 2021): 6033–49. http://dx.doi.org/10.1007/s10639-021-10542-y.

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Et. al., Sobia Wassan ,. "How Artificial Intelligence Transforms the Experience of Employees." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 10 (May 12, 2021): 7116–35. http://dx.doi.org/10.17762/turcomat.v12i10.5603.

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Artificial intelligence brings large markets, including advertising, tourism, finance, policy, workplace education. We probably associated with Chabot's job (defined as an automated, but personalized, a conversation between software and human users). We plan to use Chatbots in the workplace to assist us in pursuing a new career, addressing human resource questions, and also accepting coaching and mentoring after using them further in our personal lives. Since Chabot digitizes human resource programs, workers can access HR solutions from anywhere. HR artificial intelligence can result in a more streamlined, scalable and user-driven employee interface. To find the convergence between artificial intelligence and human resources, HR executives started using Chatbots in recruiting, staff service, staff production, and preparing to create greater value for the company. Indeed, Chabot's can be treated as the HR team's newest participant, capable of quickly finding solutions to commonly asked questions. Since we've grown accustomed to Chabot's in our everyday lives, we intend to use them at work. Artificial intelligence is changing how career applicants and workers interact. Five operational procedures are supposed to kick-start this new transformation when managers begin to implement artificial intelligence plans and roadmaps: 1. Experiment with different Chatbots to learn artificial intelligence. 2.Develop a joint strategy for HR, IT, Real Estate, Communitarians and Digital Transformation cross-functional partners; 3.Recognize how deployment can affect the technology roadmap; 4 Identify new job tasks that will make full usage of AI in HR; 5 Improve the understanding of artificial intelligence in the workplace by the HR team.

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Morelli, Michael. "THE ATHENIAN ALTAR AND THE AMAZONIAN CHATBOT: A PAULINE READING OF ARTIFICIAL INTELLIGENCE AND APOCALYPTIC ENDS." Zygon® 54, no. 1 (February 17, 2019): 177–90. http://dx.doi.org/10.1111/zygo.12483.

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Kim, Hea-Suk, Na Young Kim, and Yoonjung Cha. "Is It Beneficial to Use AI Chatbots to Improve Learners’ Speaking Performance?" Journal of AsiaTEFL 18, no. 1 (April 30, 2021): 161–78. http://dx.doi.org/10.18823/asiatefl.2021.18.1.10.161.

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Pérez, José Quiroga, Thanasis Daradoumis, and Joan Manuel Marquès Puig. "Rediscovering the use of chatbots in education: A systematic literature review." Computer Applications in Engineering Education 28, no. 6 (September 3, 2020): 1549–65. http://dx.doi.org/10.1002/cae.22326.

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Journal articles on the topic 'Educational chatbot'

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