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Verena Dornauer; Michael Netzer; Éva Kaczkó; Lisa-Maria Norz; Elske Ammenwerth – International Journal of Artificial Intelligence in Education, 2024
Cognitive presence is a core construct of the Community of Inquiry (CoI) framework. It is considered crucial for deep and meaningful online-based learning. CoI-based real-time dashboards visualizing students' cognitive presence may help instructors to monitor and support students' learning progress. Such real-time classifiers are often based on…
Descriptors: Electronic Learning, Discussion, Classification, Automation
Amine Boulahmel; Fahima Djelil; Gregory Smits – Technology, Knowledge and Learning, 2025
Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…
Descriptors: Independent Study, Educational Research, Classification, Educational Indicators
Tim M. Steininger; Jörg Wittwer; Thamar Voss – Psychology Learning and Teaching, 2025
In order to make informed instructional decisions, teachers need psychological knowledge about relational categories. We conducted two 2 x 2 experiments to examine effective designs for learning relational categories in the context of teacher education. In both experiments, a blocked compared to an interleaved example format was more beneficial…
Descriptors: Classification, Learning Processes, Student Teachers, Psychology
Antti Moilanen – Educational Theory, 2025
In this article Antti Moilanen assesses criticisms of Wolfgang Klafki's model of exemplary teaching made by Meinert Meyer and Hilbert Meyer and by Chi-Hua Chu. "Exemplary teaching" is a style of discovery-based teaching in which students study concrete examples of general principles in such a way that they acquire transferable knowledge…
Descriptors: Models, Educational Theories, Educational Philosophy, Criticism
Sarah H. Solomon; Anna C. Schapiro – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Concepts contain rich structures that support flexible semantic cognition. These structures can be characterized by patterns of feature covariation: Certain features tend to cluster in the same items (e.g., "feathers," "wings," "can fly"). Existing computational models demonstrate how this kind of structure can be…
Descriptors: Concept Formation, Learning Processes, Verbal Stimuli, Visual Stimuli
Chi Hong Leung; Winslet Ting Yan Chan – Asian Journal of Contemporary Education, 2025
This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Error Patterns
Kwaku Adu-Gyamfi; Kayla Chandler; Anthony Thompson – School Science and Mathematics, 2025
The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…
Descriptors: Algebra, Mathematics Instruction, Barriers, Cognitive Processes
Luke Strickland; Simon Farrell; Micah K. Wilson; Jack Hutchinson; Shayne Loft – Cognitive Research: Principles and Implications, 2024
In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…
Descriptors: Automation, Reliability, Man Machine Systems, Learning Processes
O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
Hoa-Huy Nguyen; Kien Do Trung; Loc Nguyen Duc; Long Dang Hoang; Phong Tran Ba; Viet Anh Nguyen – Education and Information Technologies, 2024
This article presents the results of an experiment in personalizing course content and learning activity model tailored for online courses based on students' learning styles. The main research objectives are to design and pilot a model to determine students' learning styles to create personalized online courses. The study also addressed an…
Descriptors: Models, Online Courses, Cognitive Style, Classification
Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
Sarah Berger; Laura J. Batterink – Developmental Science, 2024
Children achieve better long-term language outcomes than adults. However, it remains unclear whether children actually learn language "more quickly" than adults during real-time exposure to input--indicative of true superior language learning abilities--or whether this advantage stems from other factors. To examine this issue, we…
Descriptors: Child Language, Language Acquisition, Learning Processes, Language Skills
Nadja Beeler; Esther Ziegler; Andreas Volz; Alexander A. Navarini; Manu Kapur – Advances in Health Sciences Education, 2024
Even though past research suggests that visual learning may benefit from conceptual knowledge, current interventions for medical image evaluation often focus on procedural knowledge, mainly by teaching classification algorithms. We compared the efficacy of pure procedural knowledge (three-point checklist for evaluating skin lesions) versus…
Descriptors: Foreign Countries, Premedical Students, Undergraduate Students, Medicine
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