OPTIMIZING LEARNING WITH ARTIFICIAL INTELLIGENCE IN THE CLASSROOM: THE MEDIATING ROLE OF TIME MANAGEMENT SKILLS IN ENHANCING ACADEMIC ACHIEVEMENT AMONG UNIVERSITY STUDENTS IN KLANG VALLEY, MALAYSIA

Abstract

This study investigated how Artificial Intelligence (AI) influences academic achievement among university students in Klang Valley, Malaysia, with time management skills as a mediating factor. Grounded in Zimmerman’s Self-Regulated Learning (SRL) model, it explored the relationships between the frequency, familiarity, and duration of AI use and students’ academic performance. A quantitative design was employed using 313 valid responses from three private universities. Data were collected through a structured questionnaire and analysed using SPSS version 30 with multiple regression and Hayes PROCESS MACRO mediation tests. The findings revealed that frequent, familiar, and prolonged AI use enhanced academic performance. Time management skill mediated the relationships between AI familiarity and duration with academic performance, but not between frequency and academic performance. The study bridges theoretical and practical gaps by showing that self-regulatory behaviours strengthen the educational value of AI. It recommends integrating AI literacy with structured time management skills to optimize learning outcomes. Article visualizations: