Mapping a Decade of Research on Artificial Intelligence and Augmented Reality in Physics Education: A Bibliometric Analysis (2016–2025) - Zainuddin Zainuddin; Misbah Misbah; Mastuang Mastuang; Qamariah Qamariah; Mohd Zaidi Bin Amiruddin; Nor Farahwahidah Abdul Rahman (CV FOUNDAE, 2025)
This study presents a Scopus-based bibliometric mapping of a decade of research on Artificial Intelligence (AI) and Augmented Reality (AR) in physics education, spanning the period from 2016 to 2025. The dataset was retrieved from Scopus on August 2, 2025, and, following PRISMA-style screening and filtering, comprised 1,038 English-language journal articles at the final publication stage. Bibliometric analyses were conducted using Bibliometrix (Biblioshiny), VOSviewer, and Microsoft Excel to examine publication growth, leading sources and authors, geographic and institutional contributions, collaboration patterns, and conceptual structures through keyword co-occurrence, thematic mapping, and thematic evolution. The results indicate accelerated publication growth after 2019 and an interdisciplinary dissemination pattern across education- and technology-facing outlets. Conceptual mapping suggests that AI-related themes (e.g., adaptive and data-informed learning support) and AR-related themes (e.g., interactive visualization and representational learning) constitute the dominant pillars of the field, while physics-education-specific learning mechanisms (e.g., conceptual change, multi-representational reasoning, and inquiry/laboratory enactment) are unevenly foregrounded across clusters. Because this is a bibliometric study, the findings provide a structured overview of research patterns and thematic orientations rather than causal evidence of learning effectiveness, thereby informing future empirical and design-based studies that connect AI/AR developments to physics-education-specific learning mechanisms and implementation contexts.