Abstract

The convergence of artificial intelligence (AI) and the Internet of Things (IoT) has been advanced as the technical foundation of adaptive, sensor-rich learning environments, yet the structure and maturity of the resulting literature have not been mapped systematically. This study reports a scientometric analysis of 824 Scopus-indexed documents published between 2016 and 2025, retrieved with a TITLE-ABS-KEY query combining AI, IoT, and education and screened in accordance with the PRISMA 2020 statement. Performance analysis and science mapping were conducted with the bibliometrix R package (Biblioshiny) and VOSviewer, and comprised source, authorship, and country analyses, keyword co-occurrence, a strategic thematic map, thematic evolution across three periods, author co-citation, and a logistic life-cycle model. The corpus was produced by 2,668 authors across 525 sources, and annual output rose from a single document in 2016 to 274 in 2024. Publication is markedly dispersed: computing proceedings series and engineering outlets, rather than education journals, head the Bradford core; conference papers account for 47.1% of research documents; and author productivity departs sharply from Lotka’s law (β = 5.07), with 95.4% of authors contributing a single document. India and China dominate corresponding authorship, whereas international co-authorship remains modest at 20.87%. Artificial intelligence, the Internet of Things, and machine learning form a single central keyword cluster, while educational terms occupy peripheral clusters. The strategic map contains basic and niche themes but no motor theme, and thematic evolution shows continuous lineages for AI and IoT but none for pedagogy. Author co-citation reveals an intellectual base drawn from Industry 4.0, cyber-physical systems, and machine-learning research, with education-specific authors at its periphery. A logistic model signaled saturation (K = 869), but sensitivity analyses showed this to be an artifact of the partial 2025 year; on complete or annualized data, the field is at or just before its inflection point. The field is therefore expanding but unconsolidated, technologically driven, and reliant on an intellectual base imported from outside education. Implications for research agendas, publication strategy, and capacity building are discussed.

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