AI-Enhanced Augmented Reality Framework for Interactive Learning in Higher Education

Abstract

Augmented Reality (AR) is increasingly used in higher education to improve visualization, engagement, and practice-based learning, yet existing studies often discuss learning benefits, implementation patterns, and adoption barriers separately and provide limited guidance for AI-supported personalization. This study conducted a structured literature review using a PRISMA-guided search and screening process across Scopus, Web of Science, ScienceDirect, IEEE Xplore, and Google Scholar. Studies published from 2022 to 2026 were screened using predefined inclusion, exclusion, and quality criteria, resulting in 46 studies for synthesis across discipline, AR technology type, learning outcome domain, and pedagogical approach. The findings show consistently positive effects of AR on learning outcomes, including prior meta-analytic evidence reporting a pooled Hedges’ g of 0.896. The strongest effects were found in psychomotor learning, while cognitive and affective outcomes showed moderate to smaller gains. AR also improved attention, motivation, confidence, and satisfaction, although collaborative benefits were less consistently replicated. Based on these findings, the study proposes a five-layer AI enhanced AR learning framework integrating learner data acquisition, learning analytics, adaptive content, AR visualization, and institutional feedback within a learning factory environment. The study concludes that AR has strong potential for higher education, but successful adoption depends on infrastructure readiness, device compatibility, educator capability, and responsible data governance. The framework also supports SDG 4 and Indonesia’s MBKM agenda.