Effectiveness of a Large Language Model-Based Feedback System for Case Report Writing in Novice Rehabilitation Staff Education: A Mixed-Methods Study
DOI:
https://doi.org/10.51094/jxiv.844キーワード:
large language model、 education、 case report、 feed back抄録
Objectives: To develop a large language model (LLM) based feedback system to improve the efficiency of case report writing in novice rehabilitation staff education.
Design: A sequential mixed methods study.
Methods: We conducted a preliminary survey to identify burdensome feedback tasks and developed prompts using the Claude 3 Opus. We implemented the feedback system with Google Apps Script and Slack chatbots. Effectiveness and usability were evaluated through surveys. The study included five novice rehabilitation staff who joined our hospital in April 2024.
Results: All novice staff reported that the LLM feedback was equivalent to previous human feedback and helpful for their learning. The System Usability Scale (SUS) scores showed high usability (median: 90, range: 70-95). Three instructors (60%) agreed the system saved time and reduced guidance sessions, while four (80%) felt it would alleviate their future burden. However, opinions varied regarding the feedback content's suitability and its potential to enhance novice staff learning outcomes.
Conclusion: The LLM-based feedback system for case reports showed potential to reduce instructors' burden and provided an efficient learning environment for novice rehabilitation staff. Future research should focus on system revision and further evaluation.
This study was pre-registered in the UMIN Clinical Trials Registry (UMIN-CTR) (Trial ID: UMIN000053315). https://center6.umin.ac.jp/cgi-bin/icdr/ctr_reg_list.cgi
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The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this articleダウンロード *前日までの集計結果を表示します
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投稿日時: 2024-08-13 11:46:20 UTC
公開日時: 2024-08-16 09:00:34 UTC
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Copyright(c)2024
Tonouchi, Yuuto
Shunsuke Nakai
Kayo Nurakami
Yuki Kataoka
この作品は、Creative Commons Attribution 4.0 International Licenseの下でライセンスされています。