Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT
By Wei Dai, Jionghao Lin, Hua Jin, Tongguang Li, Yi-Shan Tsai, Dragan Gasevic, Guanliang Chen. International Conference on Advanced Learning Technologies, 2023
335 citations recorded by the source corpus.
Educational feedback has been widely acknowledged as an effective approach to improving student learning. However, scaling effective practices can be laborious and costly, which motivated researchers to work on automated feedback systems (AFS). Inspired by the recent advancements in the pre-trained language models (e.g., ChatGPT), we posit that such models might advance the existing knowledge of textual feedback generation in AFS because of their capability to offer natural-sounding and detailed responses. Therefore, we aimed to investigate the feasibility of using ChatGPT to provide students with feedback to help them learn better. Our results show that i) ChatGPT is capable of generating more detailed feedback that fluently and coherently summarizes students' performance than human instructors; ii) ChatGPT achieved high agreement with the instructor when assessing the topic of students' assignments; and iii) ChatGPT could provide feedback on the process of students completing the task, which might benefit students developing learning skills.
Subfields: Artificial Intelligence, Health Informatics
View Paper: https://www.semanticscholar.org/paper/3c996ace0fc6c54dbd9035d92d731bd9a57f8c6d
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Citations in the corpus
- Impact of AI assistance on student agency (2023, background): “Dai et al. (2023) found that ChatGPT could provide detailed and effective feedback to students, showcasing its potential to improve the feedback generation process.”
- Promises and challenges of generative artificial intelligence for human learning (2024, positive): “…(see Box 2 for key definitions of AI terms), have shown promise in automating various learning tasks 2 , delivering feedback on human efficacy 3 , outperforming average stu dents in reflective writing 4 , innovating conversational assessments 5 , creating dynamic learning resources 6 and…”
- Impact of ChatGPT on ESL students’ academic writing skills: a mixed methods intervention study (2024, background): “Fifth, self-correction was made easy (Dai et al., 2023) Last, a major factor that might have shaped EG students’ performance in the study is their pre-intervention proficiency levels.”
- New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023, background): “In addition, the instant grading provided on assessments ensures that students receive timely and constructive feedback on their performance [44,50].”