The Impact of AI-Driven Adaptive Learning on EFL Writing Performance and L۲ Grit: A Personalized Feedback Mechanism

This study aimed at investigating the effect of an artificial intelligence (AI)-driven adaptive learning system on EFL students’ writing performance, and examining how personalized feedback influences students' L۲ grit in academic writing. To this end, ۸۴ EFL students, who were selected through convenience sampling, assigned to one of the two instruction groups (AI/ face-to-face). The participants were administered an IELTS writing task and L۲ Grit Scale. During the course, the AI-based learners engaged with an AI adaptive learning platform that provided real-time personalized feedback, scaffolded writing tasks, and personalized learning trajectories, while the face-to-face group subjected to conventional instructor-based feedback. After the treatment, L۲ Grit Scale and another IELTS writing task were given. Besides, a semi-structured interview was conducted among twenty AI-based learners to explore learners’ perception towards the role of adaptive AI learning and personalized feedback for motivational shifts in L۲ grit. The results revealed the AI-based group significantly outperformed the face-to-face group in the writing posttest and demonstrated higher level of L۲ grit. Additionally, the analysis of interview indicated that the students regarded AI adaptive learning as highly effective in sustaining effort and consistency of interest because personalized feedback promotes learner autonomy, self-regulation, and resilience in mastering writing skills. The findings of this study provide theoretical contributions to adaptive learning frameworks and provide useful guidelines for educators and policymakers seeking to promote better L۲ writing performance while cultivating long-term resilience and grit.

کلیدواژه ها:

AI-driven adaptive learning ، personalized feedback ، EFL writing performance ، L۲ grit