Feedback Literacy and EFL Learner Engagement With ChatGPT Feedback: Predicting Feedback Uptake and Perceived Usefulness

Abstract

The proliferation of generative AI tools such as ChatGPT has transformed feedback provision in EFL writing, offering scalable and immediate support to learners. However, learner engagement with AI-generated feedback remains highly variable, raising questions about the internal mechanisms that shape feedback uptake. This study investigates how feedback literacy predicts both the behavioral adoption and perceived usefulness of ChatGPT-generated feedback among EFL learners, while also examining whether perceived ease of use mediates this relationship. Data were collected from 51 Chinese university students through questionnaires and revision-based tasks across three ChatGPT-supported writing assignments. Results from linear regression and bootstrapped mediation analyses revealed that feedback literacy significantly predicted both successful feedback uptake (R² = .56) and perceived usefulness (R² = .42). Moreover, perceived ease of use partially mediated this relationship, suggesting a layered cognitive-affective mechanism underlying learners’ engagement with algorithmic feedback. These findings extend feedback literacy theory beyond interpersonal contexts to AI-mediated, non-dialogic writing environments. They also refine the Technology Acceptance Model by highlighting learner competence as a critical determinant of usability and value perceptions. Pedagogically, the study underscores the need to cultivate feedback literacy as a prerequisite for meaningful engagement with AI tools in writing instruction.

Ähnliche Arbeiten