Is use of ChatGPT cheating? Students of health professions perceptions.

ChatGPT Generative AI artificial intelligence cheating higher education

Journal

Medical teacher
ISSN: 1466-187X
Titre abrégé: Med Teach
Pays: England
ID NLM: 7909593

Informations de publication

Date de publication:
04 Aug 2024
Historique:
medline: 5 8 2024
pubmed: 5 8 2024
entrez: 5 8 2024
Statut: aheadofprint

Résumé

The purpose of this study is to explore student perceptions of generative AI use and cheating in health professions education. The authors sought to understand how students believe generative AI is acceptable to use in coursework. Five faculty members surveyed students across health professions graduate programs using an updated, validated survey instrument. Students anonymously completed the survey online, which took 10-20 min. Data were then tabulated and reported in aggregate form. Nearly 400 students from twelve academic programs including health and rehabilitation science, occupational therapy, physical therapy, physician assistant studies, speech-language pathology, health administration and health informatics, undergraduate healthcare studies, nurse anesthesiology, and cardiovascular perfusion. The majority of students identify the threat of generative AI to graded assignments such as tests and papers, but many believe it is acceptable to use these tools to learn and study outside of graded assignments. Generative AI tools provide new options for students to study and learn. Graduate students in the health professions are currently using generative AI applications but are not universally aware or in agreement of how its use threatens academic integrity. Faculty should provide specific guidance on how generative AI applications may be used.

Identifiants

pubmed: 39099009
doi: 10.1080/0142159X.2024.2385667
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-5

Auteurs

Abby Swanson Kazley (AS)

Department of Health Care Leadership and Management, Medical University of South Carolina, Charleston, SC, USA.

Christine Andresen (C)

MUSC Libraries, Medical University of South Carolina, Charleston, SC, USA.

Angela Mund (A)

Department of Clinical Science, Medical University of South Carolina, Charleston, SC, USA.

Clint Blankenship (C)

Division of Physician Assistant Studies, Department of Clinical Sciences, Medical University of South Carolina, Charleston, SC, USA.

Rick Segal (R)

Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC, USA.

Classifications MeSH