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Wijaya, Adi; Setiawan, Noor Akhmad; Shapiai, Mohd Ibrahim – Electronic Journal of e-Learning, 2023
This study aims to provide a comprehensive overview of the current state and potential future research in learning style detection. With the increasing number and diversity of research in this area, a quantitative approach is necessary to map out current themes and identify potential areas for future research. To achieve this goal, a bibliometric…
Descriptors: Bibliometrics, Cognitive Style, Diagnostic Tests, Content Analysis
Mamcenko, Jelena; Kurilovas, Eugenijus; Krikun, Irina – Informatics in Education, 2019
The paper aims to present application of Educational Data Mining and particularly Case-Based Reasoning (CBR) for students profiling and further to design a personalised intelligent learning system. The main aim here is to develop a recommender system which should help the learners to create learning units (scenarios) that are the most suitable for…
Descriptors: Case Method (Teaching Technique), Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style
Saastamoinen, Kalle; Rissanen, Antti – International Baltic Symposium on Science and Technology Education, 2019
Conventional learning guidance systems are typically automated machines for creating teaching materials: quizzes, exercises, examinations etc. In the future, systems will also offer ease of use, attention to sociality, ability to adapt to the pupil's needs and skill levels, and time savings. Ease-of-use and adaptation can be sought using systems…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Artificial Intelligence, Usability
Dounas, Lamiae; Salinesi, Camille; Beqqali, Omar El – Journal of Information Technology Education: Research, 2019
Aim/Purpose: In this paper, we highlight the need to monitor and diagnose adaptive e-learning systems requirements at runtime to develop a better understanding of their behavior during learning activities and improve their design. Our focus is to reveal which learning requirements the adaptive system is satisfying while still evolving and to…
Descriptors: Electronic Learning, Learning Activities, Instructional Design, Accuracy
Wang, Ya-huei; Liao, Hung-Chang – British Journal of Educational Technology, 2011
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is…
Descriptors: Cognitive Style, Learning Motivation, Learning Processes, Individualized Instruction
Gregg, Dawn G. – Learning Organization, 2007
Purpose: The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach: This paper proposes an e-learning environment that can be used to provide customized…
Descriptors: Electronic Learning, Cognitive Style, Student Characteristics, Prior Learning
Peer reviewedMilne, Sue; Cook, Jean; Shiu, Edward; McFadyen, Angus – Educational Psychology, 1997
Reports on the development of a composite learner model for adaptive tutoring systems that combines a model of learner attributes with a simple overlay model of the learner's domain knowledge state. The system is able to select the optimal form of learning material to be presented for the subject. (MJP)
Descriptors: Cognitive Psychology, Cognitive Restructuring, Cognitive Style, Computer Uses in Education

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