Microlearning Effectiveness in Higher Education: A Systematic Review and Meta-Analysis of Student Retention and Learning Outcomes - Muhammad Jainuri; Kamid Kamid; Syaiful Syaiful; Nizlel Huda (Universitas Teknokrat Indonesia, 2025)
The proliferation of digital technologies in higher education has necessitated innovative pedagogical approaches to enhance student retention and learning outcomes. Microlearning, characterized by short, focused learning segments, has emerged as a promising strategy for addressing contemporary educational challenges. This systematic review and meta-analysis evaluates the effectiveness of microlearning interventions in higher education settings, specifically examining their impact on student retention rates and learning outcomes from 2020-2025. Following PRISMA guidelines, we comprehensively searched multiple databases, including PubMed, Scopus, Web of Science, ERIC, and IEEE Xplore. Studies were included if they examined microlearning interventions in higher education contexts with quantitative measures of student retention or learning outcomes. Quality assessment was performed using the Newcastle-Ottawa Scale and Cochrane Risk of Bias tool. Of 2,847 initially identified studies, 42 met inclusion criteria, encompassing 15,673 participants across 18 countries. Meta-analysis revealed significant positive effects of microlearning on student retention (pooled OR = 1,87; 95% CI: 1,45-2,41; p < 0,001) and learning outcomes (standardized mean difference = 0,74; 95% CI: 0,58-0,90; p < 0,001). Subgroup analyses indicated greater effectiveness in STEM subjects when combined with mobile technologies. Heterogeneity was moderate (I² = 67% for retention, I² = 71% for learning outcomes). Microlearning significantly positively affects student retention and learning outcomes in higher education. The evidence supports its implementation as an effective pedagogical strategy, particularly in statistics education and technology-enhanced learning environments. Future research should focus on long-term retention effects and optimal design principles.