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Hmedna, Brahim; Bakki, Aicha; Mezouary, Ali El; Baz, Omar – Smart Learning Environments, 2023
Massive Open Online Courses (MOOCs) are revolutionizing online education and have become a popular teaching platform. However, traditional MOOCs often overlook learners' individual needs and preferences when designing learning materials and activities, resulting in suboptimal learning experiences. To address this issue, this paper proposes an…
Descriptors: MOOCs, Student Attitudes, Preferences, Cognitive Style
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Sidney Newton; Rui Wang – Educational Studies, 2024
Notwithstanding the neuromyth controversy, the malleability of learning style preferences impacts the validity of the measurement instrument and the effectiveness of the associated model of learning. This study investigates the test-retest reliability and underlying dynamics of Kolb's Learning Style Inventory (KLSI). It surveys 245 college-level…
Descriptors: Cognitive Style, Preferences, Reliability, Validity
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Robert J. Sternberg – Gifted Education International, 2024
Individuals are typically identified as gifted largely on the basis of competence in limited contexts, but their performance in the real world, both as children and adults, often lags far behind their competence. Thus, the identification of the individuals as "gifted," however useful in theory, is much less useful in practice. This…
Descriptors: Models, Gifted, Competence, Performance
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Lin, Chieh-Peng; Chiang, Pin-Hsuan – Vocations and Learning, 2023
Drawing upon the social network theory and social cognitive theory, this research proposes a model that assesses team performance from the mediating aspect of knowledge application, which represents a team's learning process whereby an effective retrieval mechanism enables the team to access knowledge. In the model, team performance relates to…
Descriptors: Social Networks, Social Cognition, Models, Learning Processes
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Troussas, Christos; Giannakas, Filippos; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Interactive Learning Environments, 2023
Computer-Supported Collaborative Learning is a promising innovation that ameliorates tutoring through modern technologies. However, the way of recommending collaborative activities to learners, by taking into account their learning needs and preferences, is an important issue of increasing interest. In this context, this paper presents a framework…
Descriptors: Computer Assisted Instruction, Cognitive Style, Cooperative Learning, Models
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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
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Ashraf, Erum; Manickam, Selvakumar; Karuppayah, Shankar; Malik, Sufiana Khatoon – Journal of Educators Online, 2023
As the drive to move from traditional face-to-face classroom learning to e-learning is ever in demand, the knowledge corpus exposed to students can be overwhelming because there is a need to automate certain functions of the e-learning framework. One of these functions is the course recommendation feature. Course recommendations help students save…
Descriptors: Electronic Learning, Cognitive Style, Student Behavior, Course Selection (Students)
Mahmoud M. S. Abdallah; Heba Hassan Hemdan; Laila Kamel Eid Ibrahim – Online Submission, 2024
The current research paper investigates the impact of McCarthy's 4MAT model on developing writing skills among upper-grade primary pupils. Sixty-four pupils in six primary-stage grades were chosen as the study participants and were divided randomly into two matched groups (a control group and an experimental one). The researcher adopted the…
Descriptors: Elementary School Students, Models, Writing Instruction, Teaching Methods
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Xiang Wu; Huanhuan Wang; Yongting Zhang; Baowen Zou; Huaqing Hong – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate…
Descriptors: Artificial Intelligence, Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
Kimble Teresa Parkman-Colbert – ProQuest LLC, 2023
Microlearning is a relatively new educational technology that allows students to learn through short, direct segments using various modalities. The nursing profession has used microlearning to provide continuing medical education (CME). The problem addressed through this study was that instructional designers who create microlearning for medical…
Descriptors: Instructional Design, Nursing Education, Cognitive Style, Professional Continuing Education
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Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
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Rinekso, Aji Budi – Acuity: Journal of English Language Pedagogy, Literature and Culture, 2021
Learning style becomes a familiar theory for English language teachers. With a hypothesis of matching instructions and learning styles resulting in effective learning, many of the English language teachers apply learning style theory within their teaching practices. However, recent studies found that learning style is a myth since there are flaws…
Descriptors: Cognitive Style, English (Second Language), Second Language Learning, Language Teachers
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Qi Zhang – International Journal of Educational Technology in Higher Education, 2024
This study investigates how engagement (E), foreign language enjoyment (FLE), and ambiguity tolerance (AT) exert mediation/moderation in metaverse-based foreign language learning (FLL). Featuring augment/simulation-based experiences and self-fulfillment/external-control-oriented mechanics, metaverse provides virtualized interactive circumstances…
Descriptors: Second Language Learning, Second Language Instruction, Cognitive Style, Affective Behavior
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Sahin, Seyma; Ökmen, Burcu; Kiliç, Abdurrahman – Excellence in Education Journal, 2023
The purpose of this research was to evaluate the effectiveness of the brain-based learning style cycle. In the research, a pre-test and post-test quasi-experimental design without a control group was used. The research study group consisted of sophomore (2nd year) students studying at Duzce University Faculty of Education, Psychological Counseling…
Descriptors: Brain, Cognitive Style, Metacognition, Attitude Measures
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Chuah, Francis; Sze, Joyce Cheah Lynn; Keong, Ch'ng Chee; Roslan, Teh Raihana Nazirah – Journal of Language and Linguistic Studies, 2021
This study introduces a new model namely O-P-A (Optical, Physical and Acoustic) model to enhance active learning. The newly proposed model contributes to extend the current literature of the V-K-A model (Visual, Kinaesthetic and Auditory) for active learning. Three activities are implemented at three stages of the research, with each one involves…
Descriptors: Active Learning, Teaching Methods, Feedback (Response), Models
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