genai-feedback
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- PaperJournal of Second Language Writing17 Jul 2026
Can GenAI deliver growth-oriented feedback? Evidence for enhancing learners’ growth mindset and adaptive motivation in second language writing
Yuan Yao, Mi Rong, Nigel Mantou Lou
A field experiment with 92 Chinese undergraduates tested GenAI-generated growth-oriented feedback versus corrective feedback in L2 writing. Growth-oriented feedback enhanced students' growth mindset and maintained adaptive responses to mistakes, while corrective feedback reduced adaptive responses. Changes in growth mindset mediated the effects on adaptive responses and writing performance.
Original abstract
Drawing on the mindsets theory, this study explores the use of generative artificial intelligence (GenAI) in producing growth-oriented feedback (i.e., feedback that aligns with the principles of growth mindset) and investigates its impact on students’ growth mindset, adaptive responses, and second language (L2) English writing performance. This field experiment was conducted at a university in China, involving 92 first- and second-year undergraduate students ( M age = 18.76, SD =.882; 80.4% males and 19.6% females). The participants were randomly assigned to an experimental group ( n = 49) or a control group ( n = 43) and completed pre- and post-questionnaires. Over the course of a semester, the participants completed three argumentative writing tasks. After each task, the experimental group received GenAI-generated growth-oriented feedback, whereas the control group received GenAI-generated corrective feedback. The results showed that growth-oriented feedback significantly enhanced students’ growth mindset and maintained their adaptive responses to mistakes at a relatively high level. In contrast, GenAI-generated corrective feedback led to a decline in adaptive responses to mistakes. Moreover, the change in growth mindset mediated the effect of feedback types on adaptive responses and writing performance. This study offers insights into the effectiveness of GenAI in generating growth-oriented feedback, highlighting its potential of GenAI feedback in L2 writing to go beyond error correction and foster motivational, behavioral, and academic development.
- PaperAssessing Writing19 Jun 2026
When does GenAI feedback support learning? Trust calibration and verification in L2 writing assessment
Ruyang Li, Cheng Zhang, Hedi Ye
The study examines when generative AI feedback enhances learning, focusing on trust calibration and verification in L2 writing assessment.
- PaperAssessment & Evaluation in Higher Education31 May 2026
Integrating GenAI feedback and dialogic peer feedback to improve academic writing performance and revision practices: a quasi-experimental study
Sihui Li, Siyao Wang, Yating Huang
Combining GenAI feedback with dialogic peer feedback significantly improved undergraduate academic writing performance and revision practices compared to GenAI alone, which often led to partial revisions and cognitive burden. The integrated approach created a shared interpretive space that transformed students from passive recipients into agentic participants.
Original abstract
While GenAI offers unprecedented efficiency in delivering feedback, its use often reinforces transmission-oriented models that position undergraduate students as passive recipients. This study investigated how combining GenAI feedback with dialogic peer feedback influenced undergraduate students’ academic writing performance and revision behaviours through a quasi-experimental design. The results revealed that the combination of GenAI feedback and dialogic peer feedback most effectively enhanced academic writing performance and produced more sustained improvement. In addition, the GenAI feedback combined with dialogic peer feedback generated a higher frequency of full and extra revisions, whereas reliance on GenAI feedback alone more often resulted in partial revisions or non-implementation. Semi-structured interviews revealed distinct responses across conditions: GenAI feedback alone provided initial structural guidance but imposed cognitive burden and limited interpretive support; in contrast, GenAI feedback combined with dialogic peer feedback created a shared interpretive space that enabled collaborative negotiation and supported undergraduate students’ transformation from passive recipients into agentic participants. These findings advocate for student-centered approaches to GenAI integration, demonstrating how collaborative dialogue transforms GenAI output from prescriptive information into meaningful learning resources.