生成语法
数学教育
心理学
教育学
计算机科学
人工智能
作者
Thorben Jansen,Lars Höft,Luca Bahr,Johanna Fleckenstein,Jens Møller,Olaf Köller,Jennifer Meyer
出处
期刊:Psychologie in Erziehung Und Unterricht
[Ernst Reinhardt Verlag]
日期:2024-03-25
卷期号:71 (2): 80-92
被引量:7
标识
DOI:10.2378/peu2024.art08d
摘要
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.
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