Systems Research and Behavioral Science· 2026Q2
Artificial Intelligence in Education: A Systemic Scoping Review
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- 2026year
Short summary
A scoping review of 12 studies (2008-2025) reveals that while explicit use of General Systems Theory (GST) in AI in Education (AIEd) is limited, systemic perspectives are evident through concepts like complexity, feedback, adaptation, and sociotechnical interaction, framing AI integration as systemic educational change.
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Abstract
ABSTRACT This paper presents a scoping review of how Artificial Intelligence in Education (AIEd) has been conceptualized through systemic perspectives, with particular attention to direct and indirect connections with General Systems Theory (GST). It maps the existing literature, identifies research trends and highlights key issues framing systemic perspectives on AIEd. Peer‐reviewed journal articles published in English between 2008 and 2025 were searched in Scopus and ERIC, supplemented by backward and forward snowballing in Google Scholar, IEEE Xplore and Semantic Scholar. The final search, completed in June 2025, yielded a final sample of 12 studies ( n = 12). Thematic analysis, supported by qualitative coding procedures and specialized software, was applied. Findings indicate that explicit use of GST in AIEd remains limited, whereas systemic perspectives appear mainly through complexity, feedback, adaptation, sociotechnical interaction and educational transformation. This contribution clarifies AI integration as systemic educational change.
The authors' abstract, as published at the source. Systems Research and Behavioral Science, 2026 · DOI ↗
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