Does GenAI add additional value to teacher feedback on L1 learners’ reading comprehension over time? A study of immediate and delayed effects

Integrating Generative Artificial Intelligence (GenAI) into traditional teacher feedback is recommended as a potential way to improve students’ learning performance. However, empirical evidence remains limited on how GenAI-augmented teacher feedback affects students’ Classical Chinese reading comprehension across three levels (literal, interpretative, and critical), particularly regarding its immediate and delayed effects. To address this gap, this study conducted a twelve-week experiment with 72 Chinese middle school students. The experimental group (N = 35) received GenAI-augmented teacher feedback, while the control group (N = 37) received traditional teacher feedback only. An analysis of covariance (ANCOVA), using the pre-test scores as a covariate, was conducted on the three-stage reading comprehension tests (pre-test, post-test, and delayed test), complemented by post-experimental interview analysis. The results demonstrated that students who received augmented feedback experienced an initial improvement in literal and interpretative comprehension that declined over time, though the decline was slower than in the control group. This suggests that GenAI may provide additional value to teacher feedback at the levels of literal and interpretative comprehension over the longer term. Moreover, students’ critical comprehension improved in both post-test and delayed test, though the difference between the two groups was not significant, highlighting the limitations of GenAI in supplementing teacher feedback to support students’ critical comprehension. Therefore, educators should leverage GenAI for lower-level reading comprehension to support teachers while prioritising teacher-led feedback for higher-level critical reading comprehension. This study provides a theoretical basis and practical reference for effectively integrating GenAI in education.