Mapping AI related research in education through bibliometric analysis across four selected journals from 2020 to 2025

Artificial intelligence in education (AIED) has expanded rapidly since the emergence of generative artificial intelligence, yet recent development remains insufficiently mapped. This study examines publication growth, thematic change, citation impact, journal profiles and collaboration structure in AI-related research published in four selected journals between 2020 and 2025: Interactive learning environments (ILE), Computers and education: artificial intelligence (CAEAI), Journal of learning analytics (JLA) and International journal of artificial intelligence in education (IJAIED). Because three venues also publish broader educational technology research, 2719 Scopus records were screened using an explicit AI-relevance criterion; 1397 publications were retained and 1322 excluded. AI-relevant output rose from 54 publications in 2020 to 558 in 2025, a 10.3-fold increase and 59.5% compound annual growth rate. Eight predefined lexical themes matched 60.3% of the corpus and therefore provide lower-bound counts; generative AI and large language models grew from 1 publication in 2020–2021 to 307 in 2024–2025 and recorded the largest count among the eight themes. Keyword clustering placed generative AI in the motor-theme quadrant. Co-authorship analysis identified a fragmented prolific core of 74 authors in the largest connected component, divided into eight sub-groups and linked by authors with high betweenness centrality. The findings characterize AI-related literature in these four journals rather than the AIED field as a whole, and the observed growth is temporally associated with, but not shown to be caused by, the release of ChatGPT.