Artificial Intelligence in Cooperative Learning: Mapping the Intellectual Structure and Research Trajectories (2021–2025)

Abstract

Artificial intelligence (AI) is increasingly transforming cooperative learning environments, offering new possibilities for enhancing collaborative interaction and structured group engagement. This study aims to illuminate current research trends on AI-supported cooperative learning through a bibliometric analysis approach. A comprehensive examination was conducted on relevant academic works sourced from the Scopus database, covering the period from 2021 to 2025. Using the search query “artificial intelligence” AND “cooperative learning,” a total of 183 records were initially identified, with nine peer-reviewed journal articles retained following PRISMA-based screening. Various analytical tools were employed, including biblioMagika® for bibliometric indicators, OpenRefine for metadata harmonisation, and VOSviewer for keyword co-occurrence visualisation. The study analysed annual publication growth, citation patterns, source influence, authorship distribution, and thematic structures. Findings reveal a compact yet influential research base, comprising nine publications and 219 total citations, indicating strong early scholarly uptake. Results also demonstrate interdisciplinary dispersion across educational technology and engineering journals, alongside emerging thematic consolidation around artificial intelligence, cooperative learning, and analytical thinking. The study highlights both the growing academic legitimacy of AI-supported cooperative learning and the need for theoretically grounded and responsible integration within collaborative pedagogical frameworks.