Exploring EFL Learners’ Perceptions of Generative AI through the Technology Acceptance Model: Insights from an AI Literacy Program
Year: 2025
Type: conference-paper
Abstract: This study investigates how English as a Foreign Language (EFL) learners perceive the use of generative AI (GenAI) tools in their language learning, using the Technology Acceptance Model (TAM) as an analytical framework. Drawing on final reports from 41 Japanese university students who participated in a four-week AI literacy program, this study qualitatively analyzed their reflections based on TAM constructs. The analysis revealed that students experienced a wide range of benefits from using GenAI, including support for all four English skills. Notably, 83% of the sentences in the behavioral intention category expressed a positive intention to use GenAI. In the attitude construct, critical perspectives were predominant, including concerns about over-reliance, ethical risks, and privacy. Furthermore, two subcategories, namely Selective Use of GenAI and Expectations for Technological Advancement, emerged beyond the TAM framework. These reflect learners’ critical engagement and developing agency in deciding when and how to integrate GenAI tools into their studies. Additionally, students’ prior frequency of GenAI use influenced their behavioral intentions. Despite perceiving GenAI as effective during the program, those with less prior use often showed lower willingness to continue using it, citing psychological concerns or feelings of guilt. This study underscores the importance of pedagogical interventions to help learners use GenAI ethically and effectively, with an understanding of its underlying mechanisms. It also proposes extending the TAM framework to incorporate critical and reflective dimensions of technology use.
Authors: Michiyo Oda, Ryo Saito, Tatsuya Horita
Institutions: Reitaku University, Tohoku University, Tokyo Gakugei University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W7203671335