AI feedback effects on argumentative writing: The role of secondary students’ feedback receptivity and writing skills
Journal article › Research › Peer reviewed
Publication data
| By | Thorben Jansen, Hannah Pünjer, Mira Tanz, Nils-Jonathan Schaller, Lars Höft |
| Original language | English |
| Published in | Learning and Individual Differences, 131, Article 102979 |
| Pages | 12 |
| Editor (Publisher) | Elsevier |
| ISSN | 1041-6080, 1873-3425 |
| DOI/Link | https://doi.org/10.1016/j.lindif.2026.102979 |
| Publication status | Published – 10.2026 |
| Keywords | Argumentative writing, Feedback, Artificial intelligence, Receptivity to feedback |
Background:
Developing argumentative writing skills is key in secondary school. While AI feedback supports students, varying effects risk a Matthew effect. Ensuring equity requires determining which student characteristics explain differences in feedback effects.
Objective:
We investigated whether AI feedback promotes equity by examining how effects on argumentative writing varied by students' feedback receptivity and argumentative writing skills, as assumed in the student–feedback interaction model.
Method:
A total of 801 students wrote argumentative texts in a two-group experiment. For the second argumentation, the AI group received AI feedback that targets a learning progression; the control group received self-feedback prompts.
Results:
Feedback effects varied by baseline writing skills and feedback receptivity: AI (Self) feedback was most beneficial for students with lower (higher) writing skills and lower receptivity to feedback.
Conclusion:
AI feedback can benefit students who struggle to generate self-feedback during revision and thereby reduce performance gaps and foster equity.
