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Purpose As artificial intelligence (AI) becomes more embedded into higher education, it is essential to understand why some students remain sceptical. This study aims to develop and validate a scale that measures university students' distrust of AI within the context of entrepreneurship education. Design/methodology/approach A three-phase mixed-method research design was used, combining qualitative item development with quantitative psychometric validation. Data was collected from 662 business students in Catalonia using a quota-based sampling strategy. Exploratory and confirmatory factor analyses were conducted to assess the scale's dimensional structure, reliability and validity. Findings The results support a robust three-factor model of AI distrust comprising: (1) data protection distrust – contextual concerns about data use, (2) functional distrust – cognitive doubts about educational effectiveness and (3) distrust of AI replacing humans – emotional resistance to losing human interaction in learning. The final 9-item scale demonstrated strong internal consistency, convergent and discriminant validity and model fit across independent samples. Research limitations/implications Although the study is regionally focused, the findings provide a foundation for future cross-cultural validation and longitudinal research to explore how student attitudes toward AI evolve over time. Cultural and technological variables should be considered when applying the scale beyond the original context. Practical implications The scale can serve as a practical diagnostic tool for educators, curriculum designers, and developers to identify and address student distrust toward AI to ensure more inclusive AI adoption in entrepreneurship education. Originality/value This is the first validated scale specifically designed to measure student distrust of AI in entrepreneurship education, offering both theoretical and practical value to researchers and practitioners.
Smirnova et al. (Tue,) studied this question.