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…

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…

Students' academic performance prediction is one of the most important applications of Educational Data Mining (EDM) that helps to improve the quality of the education process. The attainment of student outcomes in an Outcome-based Education (OBE) system adds invaluable rewards to facilitate corrective measures to the learning processes.…

The application of gamification to the teaching-learning process across different fields of knowledge constitutes an emerging practice applied across all levels of education, from primary school up to university. This article, in keeping with the importance of the applications of this type of tool, holds the general objective of undertaking the…

The idea of using social robots for teaching and learning has become increasingly prevalent and robots are assigned various roles in different educational settings. However, there are still few authentic studies conducted over time. Our study explores teachers' perceptions of a learning activity in which a child plays a digital mathematics game…

Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…

This study argues that in developing a robust framework for students in a blended learning environment, Structural Alignment (SA) becomes the third principle of specialisation in addition to Epistemic Relation (ER) and Social Relation (SR). We provide an extended code: (ER+/-, SR+/-, SA+/-) that present strong classification and framing to the…