ChatGPT as a Learning Assistant in Medical Education Student Perceptions and Academic Performance

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

Background: Artificial intelligence-based conversational tools such as ChatGPT are increasingly being used by medical students to support learning. However, evidence regarding students' perceptions and their impact on academic performance remains limited. Aim: To evaluate medical students' perceptions of ChatGPT as a learning assistant and assess its influence on academic performance. Materials and Methods: This prospective comparative observational study was conducted over three months (December 2025 to February 2026) among 150 undergraduate medical students at a tertiary care centre in Bangalore. Participants were allocated to a ChatGPT-assisted learning group (n=75) and a conventional learning group (n=75). Academic performance was assessed using pre-test and post-test scores. Students in the ChatGPT group completed a structured perception questionnaire using a five-point Likert scale. Statistical analysis was performed using SPSS version 26.0, and a p-value <0.05 was considered statistically significant. Results: Baseline academic performance was comparable between the groups. Following the intervention, the ChatGPT-assisted group demonstrated significantly higher post-test scores (78.9 ± 7.4 vs. 69.6 ± 8.2; p<0.001) and greater improvement in academic performance. More than 90% of students reported that ChatGPT improved concept understanding, facilitated rapid clarification of difficult topics, and supported examination preparation. Overall satisfaction with ChatGPT was high, although approximately one-third of participants expressed concerns regarding occasional inaccurate responses. Conclusion: ChatGPT is an effective supplementary learning assistant that enhances academic performance, promotes self-directed learning, and is well accepted by undergraduate medical students. Appropriate faculty supervision and critical evaluation of AI-generated content remain essential for its safe and effective integration into medical education. Keywords: ChatGPT, artificial intelligence, medical education, undergraduate medical students, academic performance, student perception, self-directed learning

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