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Ke Ting Chong; Noraini Ibrahim; Sharin Hazlin Huspi; Wan Mohd Nasir Wan Kadir; Mohd Adham Isa – Journal of Information Technology Education: Research, 2025
Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…
Descriptors: Literature Reviews, Meta Analysis, Artificial Intelligence, Higher Education
Laura Froehlich; Sebastian Weydner-Volkmann – Journal of Learning Analytics, 2024
Educational disparities between traditional and non-traditional student groups in higher distance education can potentially be reduced by alleviating social identity threat and strengthening students' sense of belonging in the academic context. We present a use case of how Learning Analytics and Machine Learning can be applied to develop and…
Descriptors: Learning Analytics, Electronic Learning, Distance Education, Equal Education
Kukkar, Ashima; Mohana, Rajni; Sharma, Aman; Nayyar, Anand – Education and Information Technologies, 2023
Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…
Descriptors: Academic Achievement, Mental Health, Well Being, Interaction