AI feedback effects on argumentative writing: The role of secondary students’ feedback receptivity and writing skills
Artikel in Fachzeitschrift › Forschung › begutachtet
Publikationsdaten
| Von | Thorben Jansen, Hannah Pünjer, Mira Tanz, Nils-Jonathan Schaller, Lars Höft |
| Originalsprache | Englisch |
| Erschienen in | Learning and Individual Differences, 131, Artikel 102979 |
| Seiten | 12 |
| Herausgeber (Verlag) | Elsevier |
| ISSN | 1041-6080, 1873-3425 |
| DOI/Link | https://doi.org/10.1016/j.lindif.2026.102979 |
| Publikationsstatus | Online vorveröffentlicht – 08.2026 |
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.
