A REVIEW ON PREDICTIVE FACTORS OF ACADEMIC PERFORMANCE IN ONLINE LEARNING ENVIRONMENT

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.

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Publication Details

Journal
International Journal of Modern Education
Published
2025-06-23
DOI
https://doi.org/10.35631/ijmoe.725047
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
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article

A REVIEW ON PREDICTIVE FACTORS OF ACADEMIC PERFORMANCE IN ONLINE LEARNING ENVIRONMENT

Siew Foen Ng, Lixiu Zhang Lixiu
International Journal of Modern Education
Education and Learning Interventions
article

A REVIEW ON PREDICTIVE FACTORS OF ACADEMIC PERFORMANCE IN ONLINE LEARNING ENVIRONMENT

Siew Foen Ng, Lixiu Zhang Lixiu
article en

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.

International Journal of Modern EducationVol. 7(25)
Universiti Malaysia Kelantan (MY)
Openalex Percentile: Top 71%
Education and Learning Interventions
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