EFL student teachers’ AI self-efficacy across different countries
TL;DR
Investigation of the AI self-efficacy of English as a Foreign Language (EFL) student teachers across three distinct educational contexts reveals observable differences in AI self-efficacy scores among participants from Japan, Poland, and Slovakia.
Abstract
The rapid advancement of artificial intelligence (AI) in education has identified the need to understand how future educators perceive and engage with these technologies. This study investigates the AI self-efficacy of English as a Foreign Language (EFL) student teachers across three distinct educational contexts: Japan, Poland, and Slovakia. Recognising the crucial role of self-efficacy in technology adoption, this research aims to compare how pre-service teachers in these countries perceive their capabilities in utilising AI tools for language learning and teaching. The study employed a mixed-method design to collect quantitative data using a specifically designed evaluation scale and qualitative data via an open-ended questionnaire. The sample comprised 98 EFL student teachers from the selected countries. Results revealed observable differences in AI self-efficacy scores among participants from Japan, Poland, and Slovakia, with Japanese participants reporting higher confidence levels than their Polish and Slovak counterparts. The findings highlight a need for further research examining which contextual, educational, or experiential variables may underlie these cross-country differences.