Empirische Arbeit: Comparing Generative AI and Expert Feedback to Students’ Writing: Insights from Student Teachers

Abstract

Feedback is crucial for learning complex tasks like writing, yet its creation is time-consuming, often leading to students receiving insufficient feedback. Generative artificial intelligence, particularly Large Language Models (LLMs) like ChatGPT 3.5-Turbo, has been discussed as a solution for providing more feedback. However, there needs to be more evidence that AI-feedback already meets the quality criteria for classroom use, and studies have yet to investigate whether LLM-generated feedback already seems useful to its potential users. In our study, 89 student teachers evaluated the usefulness of feedback for students’ argumentative writing, comparing LLM against expert-generated feedback without receiving information about the feedback source. Participants rated LLM-generated feedback as useful for revision in 59% of texts (compared to 88% for expert feedback). 23% of the time, participants preferred to give LLM-generated feedback to students. Our discussion focuses on the conditions in which AI-generated feedback might be effectively and appropriately used in educational settings.