Investigating the Mediating Role of Student Engagement in the Relationship between Machine Learning-enabled Personalized Learning and Academic Performance

Abstract

The research investigates Technology Readiness (TR) and Instructor Competency in Machine Learning (ICML) and ML-Enabled Personalised Learning (MLPL) impacts on Student Learning Engagement (SLE) and Student Academic Performance (SAP) in Malaysian Higher Education Institutions (HEIs). The study analyzes SLE as a mediator which links MLPL to SAP productivity. The research assessed open and distance learning (ODL) student experiences with MLPL tools by distributing a standardized survey to 400 students across Malaysian public and private universities. SmartPLS 4.0 was used to verify measurement and structural models in the analysis process. Reliability tests involved Composite Reliability (CR) and Cronbach's Alpha (CA) analyses, whereas validity assessment utilized the Fornell-Larcker criterion together with Average Variance Extracted (AVE). Research data indicates that TR shows impact on SAP without any effect on SLE. The effects of ICML on SLE prove to be significant and positive yet the relationship between ICML and SAP remains weak to non-existent. Immediate and positive effects of MLPL occur in both SLE and SAP assessments. The effect of SLE shows partial mediation between ICML and SAP as well as between MLPL and SAP. The research did not validate that SLE serves as a mediating entity between TR and SAP. The outcomes provide crucial findings that Malaysian higher education policymakers and educators, together with administrators, can utilize. The success of MLPL depends on improving instructor competencies and TR since doing so will enhance student engagement and academic performance. This study stands out as a rare empirical investigation that combines TR with ICML along with MLPL to study their effects on student engagement and academic results in Malaysia. This research creates an integrated model for directing the strategic deployment of ML technologies in higher educational institutions.