Performance Evaluation of ChatGPT-4o on Korean Physical Therapist Licensing Examination

• 발행기관: 물리치료재활과학회
• 저자명: Bong-Su Kim Won-Seob Shin
• 간행물 정보: 『Physical Therapy Rehabilitation Science』제14권 제2호, 157~165쪽, 전체 9쪽
• 주제분류: 의약학 > 재활의학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

Objective: The objective of this study was to evaluate the performance of ChatGPT-4o on the Korean Physical TherapistLicensing Examination(KPTLE) and to explore its potential as a supplementary tool in physical therapy education and assessment. Design: Quantitative experimental study using publicly available national examination data. Methods: ChatGPT-4o was tested on 960 multiple-choice questions from the 47th to 51st KPTLE, withoutany provision of sourceor domain-specific information. Correct answer rates and pass/fail status were assessed. Additionally, its performance wascompared with that of examinees who passed the same examinations.Statistical analyses included one-sample t-tests, effect sizecalculationsusing Cohen’s d. and percentile rankings. Results: ChatGPT-4o achieved an average correct answer rate of 88.9%, consistently exceeding the passing criteria across allyears. Compared to students who passed the same examinations, ChatGPT-4o performed significantly better in overall andsubject-specific scores (p＜0.001), with large effect sizes (Cohen’s d＞0.8) and top percentile rankings. Although its performancein the medical law section was relatively poor, the overall results indicated stable and strong performance. Conclusions: ChatGPT-4o demonstrated sufficient domain knowledge to pass the written KPTLE often surpassing humanexaminee performance in standardized multiple-choice formats. These findings suggest the potential for its use in theoreticaleducation and physical therapy assessments. Additional, further research is required to assess its applicability in testing practicalskills and real-world clinical environments, particularly given the limitations inherent in current language models.

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chatgpt-4o physical therapist licensing examination artificial intelligence rehabilitation