Synthesizing Determinants of E-Learning Continuance Intention: A Meta-Analysis and Weight Analysis - Hardisem Syabrus; M.Yogi Riyantama Isjoni; Aulia Apriani; Maha Rani (AL-ISHLAH: Jurnal Pendidikan, 2025)
Understanding the factors influencing students' intention to continue using e-learning platforms is critical for sustaining digital education, especially in the post-pandemic era. While individual studies provide varying insights, a comprehensive synthesis is needed to clarify the most influential predictors of E-Learning Continuance Intention (ECI). This study conducted a systematic meta-analysis and weight analysis of 14 predictor variables related to ECI. Relevant peer-reviewed quantitative studies published between 2005 and 2022 were retrieved from Google Scholar. Inclusion criteria focused on empirical studies reporting correlation coefficients between ECI and its predictors. Meta-analysis was performed using Comprehensive Meta-Analysis Software, while weight analysis was applied to assess predictor significance based on frequency and strength of tested relationships. The findings identified Perceived Usefulness, Satisfaction, and Perceived Playfulness as best predictors, supported by both high correlation values and consistent significance across studies. Experimental predictors such as User Perception and Utility Value showed strong correlations but limited testing frequency. Four predictors, including Attitude and Social Influence, demonstrated lower predictive strength. Notably, Experiential Learning showed no significant correlation with ECI in either analysis. This study contributes to theoretical development by confirming and refining key constructs within the Expectation-Confirmation Model (ECM) in the e-learning context. The results provide practical implications for designing effective e-learning environments and highlight areas for future research, including underexplored or context-dependent predictors.