Psychometric evaluation of the Turkish version of the artificial intelligence self-efficacy scale among university students

Abstract

University students constitute a key population for assessing competence and confidence in the use of artificial intelligence (AI); however, culturally adapted and psychometrically sound instruments to measure AI self-efficacy in T & uuml;rkiye are limited. This methodological study aimed to translate, culturally adapt, and evaluate the psychometric properties of the Artificial Intelligence Self-Efficacy Scale (AISES) for Turkish university students. Data were collected between May and November 2025 via an online survey administered to 284 students from multiple universities using convenience sampling. Content validity was assessed through expert evaluation. Construct validity was examined using Exploratory and Confirmatory Factor Analyses conducted on randomly split subsamples. The analyses supported a four-factor structure explaining 73.69% of the variance, with acceptable model fit indices and excellent internal consistency (Cronbach's alpha = 0.937). The Turkish AISES demonstrated strong validity and reliability, supporting its use in assessing AI self-efficacy and informing AI-related educational initiatives among university students in T & uuml;rkiye.