Twelve tips for Natural Language Processing in medical education program evaluation

With the increasing application of Natural Language Processing (NLP) in Medicine at large, medical educators are urged to gain an understanding and implement NLP techniques within their own education programs to improve the workflow and make significant and rapid improvements in their programs. This...

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Published inMedical teacher Vol. 46; no. 9; p. 1147
Main Authors Costa-Dookhan, Kenya A, Maslej, Marta M, Donner, Kayle, Islam, Faisal, Sockalingam, Sanjeev, Thakur, Anupam
Format Journal Article
LanguageEnglish
Published England 01.09.2024
Subjects
Education, Medical - methods
Education, Medical - organization & administration
Humans
Natural Language Processing
Program Evaluation
Medical education
natural language processing
program evaluation
artificial intelligence
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Summary:With the increasing application of Natural Language Processing (NLP) in Medicine at large, medical educators are urged to gain an understanding and implement NLP techniques within their own education programs to improve the workflow and make significant and rapid improvements in their programs. This paper aims to provide twelve essential tips inclusive of both conceptual and technical factors to facilitate the successful integration of NLP in medical education program evaluation. These twelve tips range from advising on various stages of planning the evaluation process, considerations for data collection, and reflections on preprocessing of data in preparation for analysis and interpretation of results. Using these twelve tips as a framework, medical researchers, educators, and administrators will have an understanding and reference to navigating applications of NLP and be able to unlock its potential for enhancing the evaluation of their own medical education programs.
ISSN:1466-187X
DOI:10.1080/0142159X.2024.2316223