University student agency in genre-sensitive writing: a longitudinal mixed-methods multi-case study of teacher and GenAI feedback
Article / Journal
Author(s) / editor(s):
Huican Huo
,
Lawrence Jun Zhang
,
and Donglan Zhang
Year: 2026
Language(s): Emgòosj
Abstract:
This longitudinal mixed-methods multiple-case study (N=10 EFL university learners) tracked uptake of teacher and generative AI feedback across three genre-sequenced tasks and revision rounds (403 actionable points; overall uptake 55.6%). Teacher-only feedback showed higher uptake than GenAI-only (61.9% vs. 45.5%), while convergent teacher–GenAI feedback had the highest uptake (82.4%). Revision depth varied by task (analytical report showed more surface edits; argumentative essay and research proposal more meaning-level edits). Qualitative data show learners exercised evaluative judgement—adapting, rejecting, or sequencing suggestions based on epistemic risk and task demands—indicating complementary epistemic roles for teacher and GenAI feedback and agency expressed through source-sensitive, genre-sequenced coordination.
https://doi.org/10.1080/03075079.2026.2691927
Post created by: Virginia Signorini