A skill-specific perspective on AI-mediated informal digital learning of English (AI-IDLE): Examining the contributing roles of L2 writing motivation and enjoyment
Minlin Zou, Ali Soyoof, Mark Feng Teng, Huiqing Chen
Abstract
Artificial intelligence-mediated informal digital learning of English (AI-IDLE) is emerging as a promising field in computer-assisted language learning (CALL). This study asserts a need to adopt a skill-specific (e.g., writing) perspective to examine the unique challenges and psychological mechanisms associated with second language (L2) writing. Drawing upon the theoretical concepts of L2 writing future selves (i.e., the ideal L2 writing self and the ought-to L2 writing self) and L2 writing enjoyment, this study seeks to investigate the motivational and affective basis of AI-IDLE writing (AI-IDLE-W). We collected questionnaire data from 412 Chinese university students and conducted postsurvey interviews with 12 of them. The quantitative findings demonstrated that both the ideal L2 writing self and the ought-to L2 writing self can significantly influence AI-IDLE-W, but only the ideal L2 writing self can have an effect on students’ L2 writing enjoyment. Analysis of the interview data not only confirmed quantitative findings but also added nuances and contextual details to them. Furthermore, it disclosed a more dynamic and complicated mechanism of how L2 writing future selves, enjoyment, and AI-IDLE-W intertwine with each other as learners negotiate their own learning contexts. This explanatory sequential mixed-method design reveals implications for future pedagogical practices in supporting L2 learners’ writing skill development in the environment of AI-IDLE.