Effects of Individual Differences on Positive Affective Factors in AI-Assisted Language Learning: Focusing on Motivational Self System, Grit, and Enjoyment

The aim of this study was to investigate how college English learners’ individual differences in gender, prior experience with AI-based classes, and frequency of AI tool use influenced positive affective factors in AI-assisted language learning, including the L2 motivational self system, grit, and enjoyment. To address this purpose, survey data were collected from participants and analyzed using multiple regression procedures. The results indicated that among the three individual difference variables, only the frequency of AI tool use significantly predicted learners’ positive affective responses. Neither gender nor prior AI course experience showed a statistically significant relationship with the affective variables. These results suggest that regular and voluntary engagement with AI tools plays an important role in fostering positive learning emotions in AI-assisted contexts. Given that positive affect contributes to learning outcomes and language use, instructional designs should incorporate opportunities for frequent AI tool interaction. Educational programs should also provide guidance on effective AI tool utilization, tailored to learners’ needs and learning contexts. Taken together, the findings highlight the importance of behavioral engagement in shaping emotional engagement and call for future research that considers a broader set of individual difference variables to build a more comprehensive understanding of AI-assisted language learning.