<![CDATA[The COVID-19 pandemic accelerated the adoption of e-learning in elementary education, producing a rapidly expanding body of research on its effectiveness. Conventional Systematic Literature Review (SLR) procedures, built on manual, sequential PRISMA workflows, struggle to keep pace with this growth, remain vulnerable to reviewer fatigue and inconsistent screening decisions, and rarely provide appraisal criteria tailored to the developmental characteristics of young learners. This study proposes and demonstrates an innovated SLR procedure that integrates artificial-intelligence-assisted screening with a purpose-built Effectiveness Evaluation Matrix covering cognitive, affective, and behavioral indicators specific to elementary-aged students. Following an enhanced PRISMA 2020 workflow, 1,842 records were retrieved from six databases; after AI-assisted title-and-abstract screening, eligibility assessment, and Mixed Methods Appraisal Tool quality appraisal, 31 studies published between 2021 and 2026 were synthesized. Findings show that e-learning practices are most effective when they combine interactive multimedia or gamified content, structured teacher facilitation, and active parental involvement, while effectiveness declines where digital literacy and infrastructure are limited. The AI-assisted screening stage reduced manual screening workload while maintaining high sensitivity when validated against human reviewers. This innovation offers a faster, more transparent, and pedagogically grounded SLR procedure that future researchers can adapt when evaluating educational-technology interventions in primary-education contexts]]>
Copyrights © 2026
