Examining the role of Chinese language learners' grit and self-efficacy on their engagement in artificial intelligence-driven settings - Jingjing Chen (Acta Psychologica)
Background: The presentation of Artificial Intelligence (AI) in the educational domain has turned conventional learning settings into advanced tools that maximize the performance of students. Engagement is a crucial determinant of students' success in AI-driven settings. However, identifying how psychological variables like self-efficacy and grit influence engagement in such settings is an emerging area in education. Directed by Self-determination theory (SDT), the present research aims to examine the interaction between students' grit, self-efficacy, and engagement. Methods: The data were collected from 382 students in three Chinese universities with a range of academic majors. The three questionnaires were administered, and following data collection, structural equation modeling (SEM) was used to determine the model, and multiple regression analyses tested the predictive power of self-efficacy and grit on learners' engagement. Results: Grit positively predicts engagement, suggesting that learners with higher levels of perseverance and consistency are more likely to believe in their capabilities and actively participate in learning activities. In turn, self-efficacy has a direct effect on engagement, implying that confidence in one's abilities contributes meaningfully to students' engagement in academic tasks. Conclusion: The finding suggests that these two psychological constructs play a substantial and statistically significant role in shaping how actively and meaningfully students participate in AI-driven settings. Practical recommendations are aimed at enhancing learners' self-efficacy and grit, thus boosting engagement. These results contribute to a broader picture of SDT's application in AI-driven settings, offering ground for further research into motivational processes in such learning.