Artificial Intelligence in Medical Education Assessments: Navigating the Challenges to Academic Integrity

John C. Lin; Cameron A. Sabet; Christopher Chang; Ingrid U. Scott

doi:10.1007/s40670-024-02178-7

Artificial Intelligence in Medical Education Assessments: Navigating the Challenges to Academic Integrity

John C. Lin
, Cameron A. Sabet
, Christopher Chang
, Ingrid U. Scott

Research output: Contribution to journal › Comment/debate › peer-review

2 Scopus citations

Abstract

Artificial intelligence (AI) chatbots are threatening academic integrity in medical education. Potential misuse of AI chatbots to cheat has led to internet restrictions by academic institutions. We propose five strategies to mitigate this issue: (1) in-person proctored exams, (2) online proctored exams, (3) clear expectations and consequences, (4) institutional culture of integrity, and (5) addressing exam pressure. Given the limitations of these strategies, it may be necessary to consider regulations, collaboration of medical educators with AI developers, and a broader reimagining of medical education.

Original language	English (US)
Article number	e0000198
Pages (from-to)	509-512
Number of pages	4
Journal	Medical Science Educator
Volume	35
Issue number	1
DOIs	https://doi.org/10.1007/s40670-024-02178-7
State	Published - Feb 2025

All Science Journal Classification (ASJC) codes

Medicine (miscellaneous)
Education

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10.1007/s40670-024-02178-7

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title = "Artificial Intelligence in Medical Education Assessments: Navigating the Challenges to Academic Integrity",

abstract = "Artificial intelligence (AI) chatbots are threatening academic integrity in medical education. Potential misuse of AI chatbots to cheat has led to internet restrictions by academic institutions. We propose five strategies to mitigate this issue: (1) in-person proctored exams, (2) online proctored exams, (3) clear expectations and consequences, (4) institutional culture of integrity, and (5) addressing exam pressure. Given the limitations of these strategies, it may be necessary to consider regulations, collaboration of medical educators with AI developers, and a broader reimagining of medical education.",

author = "Lin, \{John C.\} and Sabet, \{Cameron A.\} and Christopher Chang and Scott, \{Ingrid U.\}",

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AU - Lin, John C.

AU - Sabet, Cameron A.

AU - Chang, Christopher

AU - Scott, Ingrid U.

N1 - Publisher Copyright: © The Author(s) under exclusive licence to International Association of Medical Science Educators 2024.

PY - 2025/2

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N2 - Artificial intelligence (AI) chatbots are threatening academic integrity in medical education. Potential misuse of AI chatbots to cheat has led to internet restrictions by academic institutions. We propose five strategies to mitigate this issue: (1) in-person proctored exams, (2) online proctored exams, (3) clear expectations and consequences, (4) institutional culture of integrity, and (5) addressing exam pressure. Given the limitations of these strategies, it may be necessary to consider regulations, collaboration of medical educators with AI developers, and a broader reimagining of medical education.

AB - Artificial intelligence (AI) chatbots are threatening academic integrity in medical education. Potential misuse of AI chatbots to cheat has led to internet restrictions by academic institutions. We propose five strategies to mitigate this issue: (1) in-person proctored exams, (2) online proctored exams, (3) clear expectations and consequences, (4) institutional culture of integrity, and (5) addressing exam pressure. Given the limitations of these strategies, it may be necessary to consider regulations, collaboration of medical educators with AI developers, and a broader reimagining of medical education.

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Artificial Intelligence in Medical Education Assessments: Navigating the Challenges to Academic Integrity

Abstract

All Science Journal Classification (ASJC) codes

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