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Journal articles on the topic 'Approaches to learning'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Urhahne, Detlef. "Learning approaches." Educational Psychology 40, no. 5 (May 27, 2020): 533–34. http://dx.doi.org/10.1080/01443410.2020.1755503.

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2

Wiltshire, Monica. "Approaches to learning." Early Years Educator 17, no. 11 (March 2, 2016): 28–30. http://dx.doi.org/10.12968/eyed.2016.17.11.28.

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Shivaleela, Barawade, Ingole Nishikant, Dahiwele Akshay, and Kokati Drakshayini. "A Study of Learning Approaches in Undergraduate Medical Students." International Journal of Toxicological and Pharmacological Research 13, no. 1 (January 30, 2023): 38–45. https://doi.org/10.5281/zenodo.11301924.

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<strong>Introduction:</strong> One among various methods adopted by students in the process of seeking knowledge is a learning approach. Learning approach of students will be of concern to the teachers and medical education experts. <strong>Methods:</strong> Total 155 second year MBBS students were included for study, out of which  143 students were participated in the study. A preformed proforma was prepared for the study which includes demographic details of the student and a R-SPQ-2F questionnaire. SPSS software was used to analysed the data. Outcome variables were described using the descriptive statistics. Mean score of two study approaches (deep & surface) was compared using the Students t-test and the internal consistency of R-SPQ-2F was assessed using Cronbach’s alpha. <strong>Results:</strong> In 130 total completed form by MBBS students 71(54.61%) were males, 59 were females (45.38%).The mean age of the students were 19.6 years. No significant difference was found in Deep and Surface learning approach in Male vs Female assessment. The deep approach score was significantly higher than those of the surface approach (33.385 Vs 24.254) (P<0.05). In subscale approaches deep motive had high score than deep strategy approaches. The cronbach’s alpha values for deep approach and surface approach were 0.668 & 0.724 respectively. The subscales had alpha values that ranged from 0.48 to 0.65. <strong>Conclusion:</strong> Our study found that learning approach preferred by students was deep approach than surface approach.

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Madeleine, Kapinga-Mutatayi, Mukendi waMpoyi Pierre, and Jan Elen. "Students Approaches to Learning: Towards a Context-specific Learning Approaches Instrument." International Journal of Higher Education 12, no. 3 (June 14, 2023): 68. http://dx.doi.org/10.5430/ijhe.v12n3p68.

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Students' Approaches to Learning (SAL) are a critical determinant of learning outcomes and have been assessed around the world, from Asia to Africa, using the traditional questionnaires developed in the Western context. However, studies in Asia have challenged the traditional dichotomous view of SAL by supporting the presence of intermediate approaches, suggesting that the current view of SAL may not be universal. In response to the need for a broader understanding of SAL, a new instrument, the Approaches to Learning Questionnaire (ALQ), was developed during a pilot study. This instrument captures both memorization and understanding in an African context, which makes it distinct from traditional instruments. Additionally, the ALQ challenges the current individualistic view of SAL by including a group dimension. Given the high psychometric quality of this new instrument, it is crucial to validate it with a large sample. Therefore, this paper discusses the validation processes and recommends the use of the ALQ for comparative purposes in the Congolese context. Further research will explore the extension of this context-specific instrument to other cultural settings and the assessment of cross-cultural validity.

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Jain, Migul. "Machine Learning and Deep Learning Approaches for Cybersecurity: A Review." International Journal of Science and Research (IJSR) 12, no. 10 (October 5, 2023): 1706–10. http://dx.doi.org/10.21275/sr231023115126.

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Axatovna, Safina Farida. "LANGUAGE LEARNING AND LANGUAGE TEACHING APPROACHES." American Journal of Philological Sciences 4, no. 3 (March 1, 2024): 43–45. http://dx.doi.org/10.37547/ajps/volume04issue03-08.

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The evolution of modern language teaching and learning can be traced back to the 20th century, a time when travel by land, sea, and air became more accessible to a larger portion of the population. Initially limited to Europe and North America, travel eventually expanded globally,allowing people from all continents to explore foreign lands. This accessibility marked a departure from the exclusive domain of pilgrims, explorers, and the wealthy, making foreign travel achievable for the majority in developed nations. Additionally, advancements such as the discovery of electricity and wireless communication facilitated global contact, irrespective of geographical location or occupation. In this article, will look at early language learning and language teaching approaches.

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Franţuzan, Ludmila, Ina Grigor, and Cristina Straistari-Lungu. "Effective school learning: conceptual and methodological approaches." Univers Pedagogic 2, no. 66 (June 15, 2020): 21–31. https://doi.org/10.5281/zenodo.4090444.

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This article examines and defines the concept of learning. The dimensions of the learning process are presented: the cognitive, emotional and social dimension and the contemporary models of learning are examined: associationist, constructivist, as information processing. It was found that the examined learning models explain the learning process from the perspective of cognitive and partially social dimensions, and the affective dimension is not addressed. So learning is approached as a specific process, only on the cognitive dimension, so it is necessary to make some changes in the educational paradigm of the learning process.

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Duff, Angus, and Sam McKinstry. "Students' Approaches to Learning." Issues in Accounting Education 22, no. 2 (May 1, 2007): 183–214. http://dx.doi.org/10.2308/iace.2007.22.2.183.

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This paper provides an overview of the students' approaches to learning (SAL) literature, including a review of the models, theories, and research instruments. SAL research has developed largely in the United Kingdom and Australasia, where its concepts are widely understood by academics. Yet little research using these ideas has been done in North America. To encourage American accounting educators to redress this imbalance, the paper describes the motivations for undertaking SAL research, describes conceptions of learning, and reviews a number of inventories developed by SAL scholars for applied research in the field. In addition, this paper traces the development of SAL research in the discipline of accounting education. Finally, the paper reviews 19 extant articles to offer suggestions for future research.

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Wasson, Barbara, and Paul A. Kirschner. "Learning Design: European Approaches." TechTrends 64, no. 6 (May 13, 2020): 815–27. http://dx.doi.org/10.1007/s11528-020-00498-0.

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Abstract Research on instructional and learning design is ‘booming’ in Europe, although there has been a move from a focus on content and the way to present it in a formal educational context (i.e., instruction), to a focus on complex learning, learning environments including the workplace, and access to learner data available in these environments. We even see the term ‘learning experience design’ (Neelen and Kirschner 2020) to describe the field. Furthermore, there is an effort to empower teachers (and even students) as designers of learning (including environments and new pedagogies), and to support their reflection on their own practice as part of their professional development (Hansen and Wasson 2016; Luckin et al. 2016; Wasson et al. 2016). While instructional design is an often heard term in the United States and refers to “translating principles of learning and instruction into plans for instructional materials, activities, information resources, and evaluation” (Smith and Ragan 1999), Europe tends to lean more towards learning design as the key for providing efficient, effective, and enjoyable learning experiences. This is not a switch from an instructivist to a constructivist view nor from a teacher-centred to a student-centred paradigm. It is, rather, a different mind-set where the emphasis is on the goal (i.e., learning) rather than the approach (i.e., instruction). Designing learning opportunities in a technology enhanced world builds on theories of human learning and cognition, opportunities provided by technology, and principles of instructional design. New technology both expands and challenges some instructional design principles by opening up new opportunities for distance collaboration, intelligent tutoring and support, seamless and ubiquitous learning and assessment technologies, and tools for thinking and thought. In this article, the authors give an account of their own and other research related to instructional and learning design, highlight related European research, and point to future research directions.

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Albergaria-Almeida, Patrícia, José Joaquim Teixeira-Dias, Mariana Martinho, and Chinthaka Balasooriya. "Kolb’s Learning Styles and Approaches to Learning." International Journal of Knowledge Society Research 1, no. 3 (July 2010): 1–16. http://dx.doi.org/10.4018/jksr.2010070101.

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The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades.This study took place during the 1st semester of the school year 2009/2010. This research was carried out in a naturalistic setting, within the context of chemistry classes for 1st year science and engineering courses, at the University of Aveiro, in Portugal. The class was composed of 100 students. At the end of the semester, the 8 chemistry students with the highest grades were selected for interview. Data was collected through Kolb’s Learning Styles Inventory, through Approaches and Study Skills Inventory for Students, through non-participant observation, through the analysis of students’ participation in online forums and lab books.The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.

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Hapsari, Shinta Ratna Yudhi, Zhafirah Azzahrawaani, Adisa Siti Nurazizah, Alif Ismail, Gina Ramdanis, Ima Siti Halimah, and Linda Angel Callista. "Learning approaches and strategies in online learning." Curricula: Journal of Curriculum Development 2, no. 1 (June 22, 2023): 113–26. http://dx.doi.org/10.17509/curricula.v2i1.53638.

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12

Cuthbert, Peter F. "The student learning process: Learning styles or learning approaches?" Teaching in Higher Education 10, no. 2 (April 2005): 235–49. http://dx.doi.org/10.1080/1356251042000337972.

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13

Abdullah, Asmawi Moch., and Samsudin. "INCREASING LEARNING OUTCOMES RHYTMIC GYMNASTICS ACTIVITIES THROUGH ACTIVE LEARNING APPROACHES." International Journal of Engineering Technologies and Management Research 6, no. 10 (October 31, 2019): 65–70. https://doi.org/10.5281/zenodo.3542259.

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The application of the rhythmic gymnastics learning approach must be in accordance with the characteristics of students, for that it requires an innovative and active learning approach according to all the existing characters. The method used is action research using Kemmis and Mc. Taggart with the design of planning, observation, action and reflection. The results showed an increase in rhythmic gymnastics learning outcomes. This is evidenced by the average in the pre cycle which is 43.2 with a percentage of 42.29%, in the first cycle increased to 63.9 with a percentage of 55.26% and in the second cycle increased to 87.3 with a percentage of 100%. So, it can be concluded that the active learning approach can improve the learning outcomes of rhythmic gymnastics. Because the application of an active learning approach is adapted to the characteristics of students who want to learn and facilitate the learning process in understanding the rhythmic gymnastics methods.

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Sharma, Divesh S. "Accounting students' learning conceptions, approaches to learning, and the influence of the learning–teaching context on approaches to learning." Accounting Education 6, no. 2 (June 1997): 125–46. http://dx.doi.org/10.1080/096392897331532.

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Karimova, Barno Ergashevna. "INNOVATIVE APPROACHES TO CREATIVE PEDAGOGY." TECHNICAL SCIENCE RESEARCH IN UZBEKISTAN 2, no. 6 (June 12, 2024): 71–75. https://doi.org/10.5281/zenodo.11624022.

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The article discusses various modern methods of creative pedagogy designed to enhance student learning and prepare them for the complexities of the future. It highlights seven innovative approaches: Project-Based Learning (PBL), STEAM Education, Flipped Classroom, Gamification, Maker Education, Inquiry-Based Learning (IBL), and Collaborative Learning.

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Rajaratnam, Navin, and SuzanneMaria D′cruz. "Learning styles and learning approaches - Are they different?" Education for Health 29, no. 1 (2016): 59. http://dx.doi.org/10.4103/1357-6283.178924.

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Ahamad, Maksud, and Nesar Ahmad. "Machine Learning Approaches to Digital Learning Performance Analysis." International Journal of Computing and Digital Systems 10, no. 1 (November 25, 2021): 963–71. http://dx.doi.org/10.12785/ijcds/100187.

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Battou, Amal, Omar Baz, and Driss Mammass. "Learning Design Approaches for Designing Virtual Learning Environments." Communications on Applied Electronics 5, no. 9 (September 26, 2016): 31–37. http://dx.doi.org/10.5120/cae2016652369.

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19

Doran, C., and R. J. Cameron. "Learning About Learning: Metacognitive Approaches in the Classroom." Educational Psychology in Practice 11, no. 2 (July 1995): 15–23. http://dx.doi.org/10.1080/0266736950110203.

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20

Javed, Abqa, Muhammad Awais, Muhammad Shoaib, Khaldoon S. Khurshid, and Mahmoud Othman. "Machine learning and deep learning approaches in IoT." PeerJ Computer Science 9 (February 6, 2023): e1204. http://dx.doi.org/10.7717/peerj-cs.1204.

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The internet is a booming sector for exchanging information because of all the gadgets in today’s world. Attacks on Internet of Things (IoT) devices are alarming as these devices evolve. The two primary areas of the IoT that should be secure in terms of authentication, authorization, and data privacy are the IoMT (Internet of Medical Things) and the IoV (Internet of Vehicles). IoMT and IoV devices monitor real-time healthcare and traffic trends to protect an individual’s life. With the proliferation of these devices comes a rise in security assaults and threats, necessitating the deployment of an IPS (intrusion prevention system) for these systems. As a result, machine learning and deep learning technologies are utilized to identify and control security in IoMT and IoV devices. This research study aims to investigate the research fields of current IoT security research trends. Papers about the domain were searched, and the top 50 papers were selected. In addition, research objectives are specified concerning the problem, which leads to research questions. After evaluating the associated research, data is retrieved from digital archives. Furthermore, based on the findings of this SLR, a taxonomy of IoT subdomains has been given. This article also identifies the difficult areas and suggests ideas for further research in the IoT.

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Alturayeif, Nouf, and Jameleddine Hassine. "Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting?" PeerJ Computer Science 11 (March 5, 2025): e2730. https://doi.org/10.7717/peerj-cs.2730.

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With the increasing reliance on machine learning (ML) across diverse disciplines, ML code has been subject to a number of issues that impact its quality, such as lack of documentation, algorithmic biases, overfitting, lack of reproducibility, inadequate data preprocessing, and potential for data leakage, all of which can significantly affect the performance and reliability of ML models. Data leakage can affect the quality of ML models where sensitive information from the test set inadvertently influences the training process, leading to inflated performance metrics that do not generalize well to new, unseen data. Data leakage can occur at either the dataset-level (i.e., during dataset construction) or at the code-level. Existing studies introduced methods to detect code-level data leakage using manual and code analysis approaches. However, automated tools with advanced ML techniques are increasingly recognized as essential for efficiently identifying quality issues in large and complex codebases, enhancing the overall effectiveness of code review processes. In this article, we aim to explore ML-based approaches for limited annotated datasets to detect code-level data leakage in ML code. We proposed three approaches, namely, transfer learning, active learning, and low-shot prompting. Additionally, we introduced an automated approached to handle the imbalance issues of code data. Our results show that active learning outperformed the other approaches with an F-2 score of 0.72 and reduced the number of needed annotated samples from 1,523 to 698. We conclude that existing ML-based approaches can effectively mitigate the challenges associated with limited data availability.

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Fyrenius, Anna, Staffan Wirell, and Charlotte Silén. "Student approaches to achieving understanding—approaches to learning revisited." Studies in Higher Education 32, no. 2 (April 2007): 149–65. http://dx.doi.org/10.1080/03075070701267194.

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Cochrane, Peter, David W. Kuecker, and Carl H. Smith. "Learning and Geometry: Computational Approaches." Mathematical Gazette 81, no. 490 (March 1997): 183. http://dx.doi.org/10.2307/3618830.

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Bekkar, Mohamed, and Taklit Akrouf Alitouche. "Imbalanced Data Learning Approaches Review." International Journal of Data Mining & Knowledge Management Process 3, no. 4 (July 31, 2013): 15–33. http://dx.doi.org/10.5121/ijdkp.2013.3402.

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Thies, Armin Paul. "Neuropsychological Approaches to Learning Disorders." Review of Research in Education 12 (1985): 91. http://dx.doi.org/10.2307/1167147.

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Duroc, Yvan. "Teaching Approaches Encouraging Autonomous Learning." Education 2, no. 4 (August 9, 2012): 96–100. http://dx.doi.org/10.5923/j.edu.20120204.06.

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Glassey, Richard, and Olle Bälter. "Sustainable Approaches for Accelerated Learning." Sustainability 13, no. 21 (October 29, 2021): 11994. http://dx.doi.org/10.3390/su132111994.

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Sustainable education does not yet have a widely accepted definition in the literature. In this work, we start from the Sustainable Development Goal of Quality Education for All (SDG4) and interpret sustainable education as increasing the quality of learning whilst conserving the resources required to produce and deliver it. From this interpretation, we argue that one path towards realising sustainable education is through the identification of teaching practices that satisfy these conditions of increased quality whilst conserving resources. We present an overview of four case studies, where the conditions for sustainable education are demonstrated through the effective use of people, processes and technologies. Each case represents an intervention that was made to improve the quality of education within an intensive three-month project, which trained immigrants to be employable in the IT industry as junior software developers. Whilst the interventions are independent and unique, they are connected by the themes of quality improvement and resource conservation. In isolation, each specific case produced improvements for both teachers and students; however, it is by combining such approaches that we can start to realise the path towards sustainable education that will help lead to a better quality of education for all. The findings of this work suggest that quality education does not come at the cost of increased resource demands; rather, approaches exist that can be considered to satisfy the conditions for sustainable education.

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Yu, Yue, Ruobing Wang, and Ruijie D. Teo. "Machine Learning Approaches for Metalloproteins." Molecules 27, no. 4 (February 14, 2022): 1277. http://dx.doi.org/10.3390/molecules27041277.

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Metalloproteins are a family of proteins characterized by metal ion binding, whereby the presence of these ions confers key catalytic and ligand-binding properties. Due to their ubiquity among biological systems, researchers have made immense efforts to predict the structural and functional roles of metalloproteins. Ultimately, having a comprehensive understanding of metalloproteins will lead to tangible applications, such as designing potent inhibitors in drug discovery. Recently, there has been an acceleration in the number of studies applying machine learning to predict metalloprotein properties, primarily driven by the advent of more sophisticated machine learning algorithms. This review covers how machine learning tools have consolidated and expanded our comprehension of various aspects of metalloproteins (structure, function, stability, ligand-binding interactions, and inhibitors). Future avenues of exploration are also discussed.

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Ahmed, Meraj, Arsheen Neda Siddiqui, and Mohammed Aamir. "NER using machine learning approaches." Global Sci-Tech 11, no. 3 (2019): 135. http://dx.doi.org/10.5958/2455-7110.2019.00019.3.

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Pun, Min. "Teaching Learning through Interdisciplinary Approaches." Crossing the Border: International Journal of Interdisciplinary Studies 5, no. 2 (July 15, 2017): 1–2. http://dx.doi.org/10.3126/ctbijis.v5i2.18432.

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There are many benefits of using interdisciplinary approaches in teaching and learning. One of the goals of teaching and learning is helping students to develop insights, problem solving skills and self-confidence. The teachers can bring them to their classroom is interdisciplinary approaches are used in the teaching learning process. In this way, interdisciplinary approaches help students develop their cognitive abilities such as skills and mental processes, which are necessary to solve the problems.Crossing the Border: International Journal of Interdisciplinary Studies 5(2) 2017: 1-2

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31

Biggs, J. B. "Assessing student approaches to learning." Australian Psychologist 23, no. 2 (July 1988): 197–206. http://dx.doi.org/10.1080/00050068808255604.

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32

Akl, Ahmad, Ahmed Moustafa, and Ibrahim El-Henawy. "Deep Learning: Approaches and Challenges." International Journal of Engineering Trends and Technology 65, no. 1 (November 25, 2018): 9–16. http://dx.doi.org/10.14445/22315381/ijett-v65p203.

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Hammer, David. "Two approaches to learning physics." Physics Teacher 27, no. 9 (December 1989): 664–70. http://dx.doi.org/10.1119/1.2342910.

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34

Yang, Shanshan, and Mike Joy. "Approaches for Learning Prolog Programming." Innovation in Teaching and Learning in Information and Computer Sciences 6, no. 4 (October 2007): 88–107. http://dx.doi.org/10.11120/ital.2007.06040088.

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35

Monostori, L., A. Markus, H. Van Brussel, and E. Westkämpfer. "Machine Learning Approaches to Manufacturing." CIRP Annals 45, no. 2 (1996): 675–712. http://dx.doi.org/10.1016/s0007-8506(18)30216-6.

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36

Jacobs, Robert A. "Integrated Approaches to Perceptual Learning." Topics in Cognitive Science 2, no. 2 (April 2010): 182–88. http://dx.doi.org/10.1111/j.1756-8765.2009.01079.x.

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37

Brodhagen, Barbara L. "Varied Teaching and Learning Approaches." Middle School Journal 29, no. 3 (January 1998): 49–52. http://dx.doi.org/10.1080/00940771.1998.11494507.

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Langley, Pat. "Approaches to learning and representation." Behavioral and Brain Sciences 13, no. 3 (September 1990): 500–501. http://dx.doi.org/10.1017/s0140525x00079875.

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Khan, Ameer Hamid, Sagar Kulkarni, Taha Mahmood, and Ameena Khan. "Evidence-based approaches to learning." Advances in Medical Education and Practice Volume 9 (August 2018): 581–82. http://dx.doi.org/10.2147/amep.s171499.

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40

Stockwell, Glenn. "Online Approaches to Learning Vocabulary." International Journal of Computer-Assisted Language Learning and Teaching 1, no. 1 (January 2011): 33–44. http://dx.doi.org/10.4018/ijcallt.2011010103.

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Examples of learning vocabulary through the computer are appearing with increasing regularity in the recent CALL literature. Much of this learning, however, tends to be teacher-centred in that learners often rely on teachers to select the vocabulary items that they are to study. In the current study, pre-intermediate learners of English studying at a university in Japan were divided into two groups: a teacher-centred (TC) group where the learners were provided with online vocabulary learning activities composed of items selected by the teacher and a learner-centred (LC) group where the learners were required to compile their own vocabulary lists which were then entered by the learners themselves into a specially designed online system that would then create the vocabulary learning activities from these items. Data were collected in the form of pre- and post-testing of vocabulary items that appeared in the teaching materials and through questionnaires regarding their perceptions of the system.

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41

Butrous, Nasir. "Business Students’ Approaches to Learning." International Journal of Learning: Annual Review 17, no. 2 (2010): 81–94. http://dx.doi.org/10.18848/1447-9494/cgp/v17i02/46856.

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Munro, Marth. "Principles for embodied learning approaches." South African Theatre Journal 31, no. 1 (January 2, 2018): 5–14. http://dx.doi.org/10.1080/10137548.2017.1404435.

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Soffi Puteh, Mohd, Nurul Ezhawati Abdul Latif, Nooriha Mansor, Yusnaliza Hamid, Sunarti Halid, and Zulkifli Ghazali. "Learning Approaches and Academic Performance." Journal of Social Sciences Research, SPI6 (December 25, 2018): 746–52. http://dx.doi.org/10.32861/jssr.spi6.746.752.

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Since Graduate on Time (GOT) being introduced as one of their key performance indicators (KPIs), certain higher education institutions are facing with situation where students are unable to complete their studies within the specified time frame. Various learning approaches have been adopted by educators in their effort to enhance students’ examination results so as to assist them to graduate on time. Studies by Tan and Laswad (2015) and Davidson (2002) have proven that learning approaches do significantly give an impact to academic performances, while Djajadikerta et al. (2008) and Chan (2011) have shown otherwise. Hence, this study is performed in order to provide further evidences concerning learning approaches and their impact onto students’ academic performance, i.e. their examination grades. Using Biggs’ (1987a) Study Process Questionnaire, 208 completed questionnaires are obtained from final semester students of Diploma in Accountancy from Faculty of Accountancy, UiTM Perak Branch, Tapah Campus. Data pertaining to their previous semesters’ grades are obtained from the online academic system and analyses are performed using SPSS. The result reveals a significant positive relationship between learning approaches and Cumulative Grade Point Average (CGPA), and it has definitely add credence to the body of knowledge pertaining this matter.

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Slavin, Robert E. "Comprehensive approaches to cooperative learning." Theory Into Practice 38, no. 2 (March 1999): 74–79. http://dx.doi.org/10.1080/00405849909543835.

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Kyndt, Eva, Elisabeth Raes, Filip Dochy, and Els Janssens. "Approaches to Learning at Work." Journal of Career Development 40, no. 4 (July 5, 2012): 271–91. http://dx.doi.org/10.1177/0894845312450776.

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Ahmed, Alhassan Ali, Mohamed Abouzid, and Elżbieta Kaczmarek. "Deep Learning Approaches in Histopathology." Cancers 14, no. 21 (October 26, 2022): 5264. http://dx.doi.org/10.3390/cancers14215264.

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The revolution of artificial intelligence and its impacts on our daily life has led to tremendous interest in the field and its related subtypes: machine learning and deep learning. Scientists and developers have designed machine learning- and deep learning-based algorithms to perform various tasks related to tumor pathologies, such as tumor detection, classification, grading with variant stages, diagnostic forecasting, recognition of pathological attributes, pathogenesis, and genomic mutations. Pathologists are interested in artificial intelligence to improve the diagnosis precision impartiality and to minimize the workload combined with the time consumed, which affects the accuracy of the decision taken. Regrettably, there are already certain obstacles to overcome connected to artificial intelligence deployments, such as the applicability and validation of algorithms and computational technologies, in addition to the ability to train pathologists and doctors to use these machines and their willingness to accept the results. This review paper provides a survey of how machine learning and deep learning methods could be implemented into health care providers’ routine tasks and the obstacles and opportunities for artificial intelligence application in tumor morphology.

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Shavelson, Richard J., and Tina Seidel. "Approaches in measuring learning environments." Learning Environments Research 9, no. 3 (January 9, 2007): 195–97. http://dx.doi.org/10.1007/s10984-006-9010-z.

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Kunigami, Masaaki. "Interdisciplinary Approaches to Learning Informatics." Journal of Systemics, Cybernetics and Informatics 21, no. 4 (December 2023): 18–22. http://dx.doi.org/10.54808/jsci.21.04.18.

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This paper discusses new challenges in learning informatics from an interdisciplinary perspective. As topics of learning informatics must cover very wide ranges, this paper will provide an overview with a combination of several ideas and applications. From a methodological point of view, the challenges include the concepts of 'knowledge networks', 'learner personas', and 'visualization of the experience'. From the viewpoints of educational applications, they contain the concepts of 'class design', 'peer review' and 'case learning'. The introduction of various concepts from fields such as computer sciences, marketing research, and design thinking of soft systems domains, whose areas are far from education applications, would add new insights to learning informatics research.

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Md Boktiar Hossain and Khandoker Hoque. "Machine Learning approaches in IDS." International Journal of Science and Research Archive 7, no. 2 (December 30, 2022): 706–15. https://doi.org/10.30574/ijsra.2022.7.2.0303.

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With the rapid expansion of digital infrastructures, cybersecurity threats have become increasingly sophisticated, necessitating advanced protection mechanisms. Traditional security solutions, such as firewalls and rule-based intrusion detection systems (IDS), often fail to detect evolving attack patterns. Machine Learning (ML) has emerged as promising approaches for enhancing IDS capabilities by identifying anomalies and predicting cyber threats with higher accuracy. This paper provides a comprehensive review of ML methodologies applied to intrusion detection systems, focusing on their effectiveness, challenges, and future directions. Despite their advancements, ML based IDS face several challenges, including data imbalance, high computational complexity, and adversarial attacks that manipulate detection mechanisms. The lack of interpretability in deep learning models hinders their deployment in critical security infrastructures. To address these limitations, future research should focus on explainable AI, federated learning for decentralized threat intelligence, and integration with blockchain technology for enhanced data integrity.

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Esanova, Nafosat Fakhriddinovna, Yodgor Behzodovich Suyarkulov, and Gulmira Sayfiddin kizi Akhatova. "DIFFERENT APPROACHES TO LEARNING MATHEMATICS." Educational Research in Universal Sciences 4, no. 2 (January 31, 2025): 154–57. https://doi.org/10.5281/zenodo.14833927.

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<em>Mathematics is a fundamental subject that plays a crucial role in various fields, including science, engineering, economics, and technology. Developing strong mathematical skills is essential for logical reasoning, problem-solving, and analytical thinking. However, different learners have different needs and preferences, which is why multiple approaches to learning mathematics exist. This document explores various methods used to teach and learn mathematics, their benefits, challenges, and how they can be combined for optimal learning outcomes.</em>

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