ArticleScientific reports2026
Development and validation of an AI use scale for sport and exercise science students.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Artificial intelligence (AI) is rapidly transforming sport and exercise domains. Yet, sport-science curricula have lagged in integrating AI literacy, and little is known about students’ knowledge, ethical practices, and perceptions regarding AI. Existing measurement tools are often generic and ill-suited to sport education contexts. This study aimed to develop and validate a concise, domain-specific questionnaire to assess sport students’ AI use. A systematic instrument development process was used, including literature review, expert consultation, item generation, and psychometric validation. The resulting 14-item tool covers four domains: AI Awareness, Ethics & Disclosure, Trust & Verification, and Course & Institution Expectations. The instrument was administered to 864 undergraduate sport-science students in China and analysed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) on separate training and test sets. EFA supported a four-factor structure with high sampling adequacy (KMO = 0.95) and strong communalities. CFA confirmed good model fit (CFI = 1.00, TLI = 0.99, RMSEA = 0.09, SRMR = 0.05). Subscales demonstrated excellent internal consistency (Cronbach’s α = 0.90–0.94; McDonald’s ω = 0.90–0.94), convergent validity (AVE = 0.77–0.87), and discriminant validity (HTMT ratios < 0.85). This validated, context-specific instrument provides educators with a reliable tool to assess and enhance AI literacy in sport education. The findings support the integration of targeted AI training, ethical instruction, and institutional policies to prepare students for responsible, real-world AI engagement in sport and health domains.
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