Psychometric validation of the AI academic phobia scale for pre-service teachers: A confirmatory factor analysis

The increasing integration of artificial intelligence into education has created new opportunities for teaching and learning while introducing psychological challenges that may influence AI adoption among future educators. This study aimed to develop and psychometrically validate the AI Academic Phobia Scale, a multidimensional instrument designed to assess AI-related psychological responses among pre-service teachers. A quantitative cross-sectional survey was conducted with pre-service teachers from teacher education institutions in India. The scale was developed using a systematic psychometric approach that included theory-driven item generation, expert review, face validation, exploratory factor analysis, confirmatory factor analysis, and comprehensive assessments of reliability and validity. The findings supported a four-dimensional structure comprising Learning Anxiety, Professional Threat Fear, Ethical and Privacy Concern, and Low AI Self-Efficacy. The confirmatory analysis supported the measurement model, with a satisfactory overall fit. Reliability and validity were supported through internal consistency, composite reliability, convergent validity, and discriminant validity procedures. The findings demonstrate that the scale is a reliable and valid instrument for assessing AI-related psychological barriers among pre-service teachers. For teacher education institutions, the instrument serves as a practical diagnostic tool to identify readiness gaps before designing AI-focused professional development. For curriculum developers, it provides an evidence base to embed AI literacy, ethical reasoning, and data privacy content into teacher preparation programs. For researchers and policymakers, it offers a validated measure to track AI readiness over time and across institutional and cultural contexts, aligned with national and international priorities for digital transformation in education.