A Review on Predictive Factors of Academic Performance in Online Learning Environment
Year: 2025
Type: article
Study design: Systematic Review
Abstract: Higher education institutions deeply integrate online learning platforms into their curricula. Learning management systems (LMS) are a core component of online learning in higher education, facilitating instruction, communication, and assessment. However, students vary significantly in their online learning effectiveness, triggering a significant amount of research on the factors that influence the predictors of academic performance. This paper provides a comprehensive review of predictors of student achievement in online learning by systematically searching and screening the literature between 2021 and 2024 in multiple academic databases, resulting in the inclusion of 27 high-quality studies. It was found that the existing literature focuses on three main areas: behavioural prediction, psychological prediction and technological prediction. However, although each of these factors is considered to be closely related to student performance, current research tends to explore them from an isolated perspective, ignoring the dynamic chain of linkages between technology, psychology, behaviour and performance. Therefore, future research should build an integrated model to explore how the characteristics of LMS platforms affect students' psychological state and behaviours, and ultimately affect learning outcomes, so as to provide theoretical support and practical guidance for improving the quality of online education.
Authors: Lixiu Zhang Lixiu, Siew Foen Ng
Institution: Universiti Malaysia Kelantan
Language: English
Topic: Online and Blended Learning
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4412918342