Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions
<p dir="ltr">The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on...
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2023
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| _version_ | 1864513523910967296 |
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| author | Alaa Abd-alrazaq (17058018) |
| author2 | Rawan AlSaad (14159019) Dari Alhuwail (6497858) Arfan Ahmed (17541309) Padraig Mark Healy (17541756) Syed Latifi (9021512) Sarah Aziz (17541312) Rafat Damseh (14440893) Sadam Alabed Alrazak (17541759) Javaid Sheikh (5534825) |
| author2_role | author author author author author author author author author |
| author_facet | Alaa Abd-alrazaq (17058018) Rawan AlSaad (14159019) Dari Alhuwail (6497858) Arfan Ahmed (17541309) Padraig Mark Healy (17541756) Syed Latifi (9021512) Sarah Aziz (17541312) Rafat Damseh (14440893) Sadam Alabed Alrazak (17541759) Javaid Sheikh (5534825) |
| author_role | author |
| dc.creator.none.fl_str_mv | Alaa Abd-alrazaq (17058018) Rawan AlSaad (14159019) Dari Alhuwail (6497858) Arfan Ahmed (17541309) Padraig Mark Healy (17541756) Syed Latifi (9021512) Sarah Aziz (17541312) Rafat Damseh (14440893) Sadam Alabed Alrazak (17541759) Javaid Sheikh (5534825) |
| dc.date.none.fl_str_mv | 2023-06-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.2196/48291 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Large_Language_Models_in_Medical_Education_Opportunities_Challenges_and_Future_Directions/30256735 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Medical biotechnology Education Curriculum and pedagogy Information and computing sciences Artificial intelligence Large language models Artificial intelligence Medical education ChatGPT GPT-4 Generative AI Students Educators |
| dc.title.none.fl_str_mv | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on a wealth of professional and academic experience, we propose that LLMs hold promise for revolutionizing medical curriculum development, teaching methodologies, personalized study plans and learning materials, student assessments, and more. However, we also critically examine the challenges that such integration might pose by addressing issues of algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, and copyright concerns in medical education. As we navigate the shift from an information-driven educational paradigm to an artificial intelligence (AI)–driven educational paradigm, we argue that it is paramount to understand both the potential and the pitfalls of LLMs in medical education. This paper thus offers our perspective on the opportunities and challenges of using LLMs in this context. We believe that the insights gleaned from this analysis will serve as a foundation for future recommendations and best practices in the field, fostering the responsible and effective use of AI technologies in medical education.</p><h2>Other Information</h2><p dir="ltr">Published in: JMIR Medical Education<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.2196/48291" target="_blank">https://dx.doi.org/10.2196/48291</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_0fe1fc9111c265989396ed1f2835b8fa |
| identifier_str_mv | 10.2196/48291 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30256735 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Large Language Models in Medical Education: Opportunities, Challenges, and Future DirectionsAlaa Abd-alrazaq (17058018)Rawan AlSaad (14159019)Dari Alhuwail (6497858)Arfan Ahmed (17541309)Padraig Mark Healy (17541756)Syed Latifi (9021512)Sarah Aziz (17541312)Rafat Damseh (14440893)Sadam Alabed Alrazak (17541759)Javaid Sheikh (5534825)Biomedical and clinical sciencesMedical biotechnologyEducationCurriculum and pedagogyInformation and computing sciencesArtificial intelligenceLarge language modelsArtificial intelligenceMedical educationChatGPTGPT-4Generative AIStudentsEducators<p dir="ltr">The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on a wealth of professional and academic experience, we propose that LLMs hold promise for revolutionizing medical curriculum development, teaching methodologies, personalized study plans and learning materials, student assessments, and more. However, we also critically examine the challenges that such integration might pose by addressing issues of algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, and copyright concerns in medical education. As we navigate the shift from an information-driven educational paradigm to an artificial intelligence (AI)–driven educational paradigm, we argue that it is paramount to understand both the potential and the pitfalls of LLMs in medical education. This paper thus offers our perspective on the opportunities and challenges of using LLMs in this context. We believe that the insights gleaned from this analysis will serve as a foundation for future recommendations and best practices in the field, fostering the responsible and effective use of AI technologies in medical education.</p><h2>Other Information</h2><p dir="ltr">Published in: JMIR Medical Education<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.2196/48291" target="_blank">https://dx.doi.org/10.2196/48291</a></p>2023-06-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.2196/48291https://figshare.com/articles/journal_contribution/Large_Language_Models_in_Medical_Education_Opportunities_Challenges_and_Future_Directions/30256735CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/302567352023-06-01T00:00:00Z |
| spellingShingle | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions Alaa Abd-alrazaq (17058018) Biomedical and clinical sciences Medical biotechnology Education Curriculum and pedagogy Information and computing sciences Artificial intelligence Large language models Artificial intelligence Medical education ChatGPT GPT-4 Generative AI Students Educators |
| status_str | publishedVersion |
| title | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| title_full | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| title_fullStr | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| title_full_unstemmed | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| title_short | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| title_sort | Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions |
| topic | Biomedical and clinical sciences Medical biotechnology Education Curriculum and pedagogy Information and computing sciences Artificial intelligence Large language models Artificial intelligence Medical education ChatGPT GPT-4 Generative AI Students Educators |