Artificial intelligence, student engagement, well-being and self-regulated learning in school education: Systematic review dataset and supplementary analytical materials
This record contains the dataset and supplementary materials of a systematic literature review examining how artificial intelligence (AI) applications used in school education relate to students' engagement, psychological and socio-emotional well-being, and self-regulated learning (SRL), the pedagogical and psychological mechanisms through which these effects are reported to occur, and the contextual, learner-related, teacher-related and technological conditions that shape them. The review covers early childhood, primary, lower and upper secondary, vocational and special education settings; higher education was excluded by design. Records were retrieved from Scopus, Web of Science, ERIC and APA PsycInfo (EBSCO) using a search string combining AI-related terms (e.g., artificial intelligence, machine learning, learning analytics, intelligent tutoring, adaptive learning, chatbots, conversational agents, generative AI, large language models), school-education and population terms, and well-being, emotional, motivational, engagement and self-regulation terms. After the application of formal filters (peer-reviewed journal articles, full-text availability, English or Italian language, publication year ≥ 2014), 4,304 records were retained; following duplicate removal, 3,624 records were screened by title and abstract, 130 full-text reports were assessed for eligibility, and 84 empirical studies were included. Screening was conducted independently by multiple reviewers, and inter-rater agreement data for both screening stages are provided. Annex A (Systematic Dataset) contains the extraction codebook, the PRISMA flow data with reasons for full-text exclusion, the bibliographic records exported from each database, the screening decisions at the first (title/abstract) and second (full-text) stages, the inter-rater agreement data, and the list of included articles. Annex B (Supplementary Material) contains the list of included studies (Table S1), the analytical codebook with operational definitions and inclusion/boundary rules (Table S2), the code-document matrices exported from ATLAS.ti for each research question and analytical domain, the characteristics of the included studies (geographical area, research methodology, AI system, educational context), and the outcome × mechanism co-occurrence analyses (absolute co-occurrence, conditional percentages, Jaccard similarity, phi coefficients, interpretive summary and heatmap data).