Assessing EFL learners’ attitudes on Generative Artificial Intelligence: Development and validation of Generative Artificial Intelligence attitude scale for EFL learners (GenAIAS)

Abstract

Generative Artificial Intelligence (GenAI) has emerged as a transformative force in education, particularly in the context of English as a Foreign Language (EFL) instruction. This study aims to develop and validate the Generative Artificial Intelligence Attitude Scale (GenAIAS) to assess EFL learners’ attitudes toward GenAI. The research involved two independent samples of university students in Türkiye, with data collected through scales and analyzed using exploratory and confirmatory factor analyses. The final scale, comprising 33 items, was categorized into four factors: Learning/Utility, Enjoyment, Usefulness, and Interest. The scale demonstrated good psychometric properties, including satisfactory convergent and discriminant validity, internal consistency, and measurement invariance across genders. The findings indicate no significant gender differences in attitudes toward GenAI, suggesting a general acceptance of GenAI technologies among EFL learners. Additionally, a positive correlation was observed between daily internet usage and attitudes toward GenAI. This study contributes to the growing body of knowledge on GenAI in language education and offers practical implications for integrating GenAI into language learning, highlighting the importance of fostering positive attitudes for successful technology adoption. Future research should further validate the scale with diverse populations to enhance its reliability and applicability.