<![CDATA[This study maps the research landscape of Artificial Intelligence and Internet of Things (AI-IoT) in physics education and identifies directions for future research. A bibliometric design combining performance analysis and science mapping was applied to 1,566 Scopus-indexed journal articles published between 2016 and 2026, selected following the PRISMA 2020 procedure. Five research questions guided the analysis: dataset profile and growth, country productivity and collaboration, intellectual base, conceptual structure, and thematic evolution. The corpus is young and growing quickly (annual growth rate 83.38%; average document age 1.44 years) and dispersed across 549 sources. China is the most productive country (286 articles), followed by Saudi Arabia, Indonesia, and the USA, while international co-authorship is only 28.67%. Co-citation analysis reveals two intellectual bases, namely AI in education and generative AI, and technology acceptance and survey methodology. Keyword mapping and thematic evolution show a shift from computer-aided instruction and machine learning toward learning systems, ChatGPT, and generative AI, whereas physics-specific and IoT terms remain peripheral. The findings point to the need for physics-grounded, pedagogically validated AI-IoT studies, particularly on sensor-based experiments, learning outcomes, generative AI, and data privacy, supported by broader international collaboration.]]>
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