ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study

Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy informati...

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Main Authors: Arun, Gautham, Perumal, Vivek, Urias, Francis Paul John Bato, Ler, Yan En, Tan, Bryan Wen Tao, Vallabhajosyula, Ranganath, Tan, Emmanuel, Ng, Olivia, Ng, Kian Bee, Mogali, Sreenivasulu Reddy
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
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Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/180408
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1804082024-10-13T15:38:05Z ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study Arun, Gautham Perumal, Vivek Urias, Francis Paul John Bato Ler, Yan En Tan, Bryan Wen Tao Vallabhajosyula, Ranganath Tan, Emmanuel Ng, Olivia Ng, Kian Bee Mogali, Sreenivasulu Reddy Lee Kong Chian School of Medicine (LKCMedicine) Medicine, Health and Life Sciences Anatomical education Artificial intelligence Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and intelligent chatbot (Anatbuddy) through an Open AI Application Programming Interface (API) that enables seamless AI-driven interactions within a secured cloud infrastructure. Anatbuddy was programmed through a Retrieval Augmented Generation (RAG) method to provide context-aware responses to user queries based on a predetermined knowledge base. To compare their outputs, various queries (i.e., prompts) on thoracic anatomy (n = 18) were fed into Anatbuddy and ChatGPT 3.5. A panel comprising three experienced anatomists evaluated both tools' responses for factual accuracy, relevance, completeness, coherence, and fluency on a 5-point Likert scale. These ratings were reviewed by a third party blinded to the study, who revised and finalized scores as needed. Anatbuddy's factual accuracy (mean ± SD = 4.78/5.00 ± 0.43; median = 5.00) was rated significantly higher (U = 84, p = 0.01) than ChatGPT's accuracy (4.11 ± 0.83; median = 4.00). No statistically significant differences were detected between the chatbots for the other variables. Given ChatGPT's current content knowledge limitations, we strongly recommend the anatomy profession develop a custom AI chatbot for anatomy education utilizing a carefully curated knowledge base to ensure accuracy. Further research is needed to determine students' acceptance of custom chatbots for anatomy education and their influence on learning experiences and outcomes. Nanyang Technological University Submitted/Accepted version This project is supported by a Special Project Grant from the Medical Education, Research and Scholarship Unit, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore. 2024-10-07T05:08:00Z 2024-10-07T05:08:00Z 2024 Journal Article Arun, G., Perumal, V., Urias, F. P. J. B., Ler, Y. E., Tan, B. W. T., Vallabhajosyula, R., Tan, E., Ng, O., Ng, K. B. & Mogali, S. R. (2024). ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study. Anatomical Sciences Education, 17(7), 1396-1405. https://dx.doi.org/10.1002/ase.2502 1935-9772 https://hdl.handle.net/10356/180408 10.1002/ase.2502 39169464 2-s2.0-85201691243 7 17 1396 1405 en Anatomical Sciences Education © 2024 American Association for Anatomy. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1002/ase.2502. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Medicine, Health and Life Sciences
Anatomical education
Artificial intelligence
spellingShingle Medicine, Health and Life Sciences
Anatomical education
Artificial intelligence
Arun, Gautham
Perumal, Vivek
Urias, Francis Paul John Bato
Ler, Yan En
Tan, Bryan Wen Tao
Vallabhajosyula, Ranganath
Tan, Emmanuel
Ng, Olivia
Ng, Kian Bee
Mogali, Sreenivasulu Reddy
ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
description Large Language Models (LLMs) have the potential to improve education by personalizing learning. However, ChatGPT-generated content has been criticized for sometimes producing false, biased, and/or hallucinatory information. To evaluate AI's ability to return clear and accurate anatomy information, this study generated a custom interactive and intelligent chatbot (Anatbuddy) through an Open AI Application Programming Interface (API) that enables seamless AI-driven interactions within a secured cloud infrastructure. Anatbuddy was programmed through a Retrieval Augmented Generation (RAG) method to provide context-aware responses to user queries based on a predetermined knowledge base. To compare their outputs, various queries (i.e., prompts) on thoracic anatomy (n = 18) were fed into Anatbuddy and ChatGPT 3.5. A panel comprising three experienced anatomists evaluated both tools' responses for factual accuracy, relevance, completeness, coherence, and fluency on a 5-point Likert scale. These ratings were reviewed by a third party blinded to the study, who revised and finalized scores as needed. Anatbuddy's factual accuracy (mean ± SD = 4.78/5.00 ± 0.43; median = 5.00) was rated significantly higher (U = 84, p = 0.01) than ChatGPT's accuracy (4.11 ± 0.83; median = 4.00). No statistically significant differences were detected between the chatbots for the other variables. Given ChatGPT's current content knowledge limitations, we strongly recommend the anatomy profession develop a custom AI chatbot for anatomy education utilizing a carefully curated knowledge base to ensure accuracy. Further research is needed to determine students' acceptance of custom chatbots for anatomy education and their influence on learning experiences and outcomes.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Arun, Gautham
Perumal, Vivek
Urias, Francis Paul John Bato
Ler, Yan En
Tan, Bryan Wen Tao
Vallabhajosyula, Ranganath
Tan, Emmanuel
Ng, Olivia
Ng, Kian Bee
Mogali, Sreenivasulu Reddy
format Article
author Arun, Gautham
Perumal, Vivek
Urias, Francis Paul John Bato
Ler, Yan En
Tan, Bryan Wen Tao
Vallabhajosyula, Ranganath
Tan, Emmanuel
Ng, Olivia
Ng, Kian Bee
Mogali, Sreenivasulu Reddy
author_sort Arun, Gautham
title ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
title_short ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
title_full ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
title_fullStr ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
title_full_unstemmed ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study
title_sort chatgpt versus a customized ai chatbot (anatbuddy) for anatomy education: a comparative pilot study
publishDate 2024
url https://hdl.handle.net/10356/180408
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