Examining the Threat of ChatGPT to the Validity of Short Answer Assessments in an Undergraduate Medical Program

克朗巴赫阿尔法 布鲁姆分类学 心理学 分类学(生物学) 认知 班级(哲学) 数学教育 医学教育 临床心理学 计算机科学 心理测量学 医学 人工智能 生态学 精神科 生物
作者
Leo Morjaria,Levi Burns,Keyna Bracken,Quang Ngo,Mark Lee,Anthony J Levinson,J. Smith,Penelope Thompson,Matthew Sibbald
出处
期刊:Journal of medical education and curricular development [SAGE]
卷期号:10 被引量:6
标识
DOI:10.1177/23821205231204178
摘要

OBJECTIVES ChatGPT is an artificial intelligence model that can interpret free-text prompts and return detailed, human-like responses across a wide domain of subjects. This study evaluated the extent of the threat posed by ChatGPT to the validity of short-answer assessment problems used to examine pre-clerkship medical students in our undergraduate medical education program. METHODS Forty problems used in prior student assessments were retrieved and stratified by levels of Bloom's Taxonomy. Thirty of these problems were submitted to ChatGPT-3.5. For the remaining 10 problems, we retrieved past minimally passing student responses. Six tutors graded each of the 40 responses. Comparison of performance between student-generated and ChatGPT-generated answers aggregated as a whole and grouped by Bloom's levels of cognitive reasoning, was done using t-tests, ANOVA, Cronbach's alpha, and Cohen's d. Scores for ChatGPT-generated responses were also compared to historical class average performance. RESULTS ChatGPT-generated responses received a mean score of 3.29 out of 5 (n = 30, 95% CI 2.93-3.65) compared to 2.38 for a group of students meeting minimum passing marks (n = 10, 95% CI 1.94-2.82), representing higher performance ( P = .008, η 2 = 0.169), but was outperformed by historical class average scores on the same 30 problems (mean 3.67, P = .018) when including all past responses regardless of student performance level. There was no statistically significant trend in performance across domains of Bloom's Taxonomy. CONCLUSION While ChatGPT was able to pass short answer assessment problems spanning the pre-clerkship curriculum, it outperformed only underperforming students. We remark that tutors in several cases were convinced that ChatGPT-produced responses were produced by students. Risks to assessment validity include uncertainty in identifying struggling students and inability to intervene in a timely manner. The performance of ChatGPT on problems requiring increasing demands of cognitive reasoning warrants further research.
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