TITLE:
The Transfer of Junior High School Students’ English Writing in the Context of Generative AI Feedback and Its Relationship with Feedback Literacy and Self-Regulated Learning
AUTHORS:
Xiaoqing Sheng
KEYWORDS:
Generative Artificial Intelligence, English Writing, Writing Transfer, Feedback Literacy, Self-Regulated Learning, Junior High School Student
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.14 No.11,
November
12,
2026
ABSTRACT: To investigate the transfer performance of junior high school students’ English writing under the condition of generative artificial intelligence feedback and its relationship with feedback literacy and self-regulated learning, 82 eighth-grade students were selected as the subjects, and the independent writing performance under the two teaching schemes of generative AI feedback and teacher feedback was compared using the unequal pre-test-post-test-delayed calibration experimental design of two natural classes, and the analysis was carried out in combination with questionnaires, feedback judgment tasks, and revised records. The results show that after controlling for pre-test writing scores, the adjusted average delayed-transfer score in the AI feedback class is 5.99 points higher than in the teacher feedback class (P = 0.002). There is a positive correlation between the change in feedback literacy and delayed transfer performance (r = 0.413, P