Using LLMs to bring evidence-based feedback into the classroom: AI-generated feedback increases secondary students’ text revision, motivation, and positive emotions
Leibniz Institute for Science and Mathematics Education · University of Hildesheim
Abstract
Writing proficiency is an essential skill for upper secondary students that can be enhanced through effective feedback. Creating feedback on writing tasks, however, is time-intensive and presents a challenge for educators, often resulting in students receiving insufficient or no feedback. The advent of text-generating large language models (LLMs) offers a promising solution, namely, automated evidence-based feedback generation. Yet, empirical evidence from randomized controlled studies about the effectiveness of LLM-generated feedback is missing. To address this issue, the current study compared the effectiveness of LLM-generated feedback to no feedback. A sample of N = 459 upper secondary students of English…
Citation impact
- FWCI
- 38.52
- Percentile
- 100%
- References
- 116
Authors
7- JMJennifer MeyerCorresponding
Leibniz Institute for Science and Mathematics Education
- TJThorben Jansen
Leibniz Institute for Science and Mathematics Education
- RSRonja Schiller
Leibniz Institute for Science and Mathematics Education
- LWLucas W. Liebenow
Leibniz Institute for Science and Mathematics Education
- MSMarlene Steinbach
Leibniz Institute for Science and Mathematics Education
Topics & keywords
- Psychology
- Positive feedback
- Social psychology
- Mathematics education
- Engineering
- Quality Education