AI支援による問題解決能力と、医学部生におけるインターネット検索エンジンおよび電子書籍との比較：横断研究

科学分野:

• Medical Education Technology; Artificial Intelligence in Healthcare; Educational Assessment

背景:

• Artificial intelligence (AI), especially large language models (LLMs), is increasingly impacting medical education.; The effectiveness of AI-LLMs for students with diverse prior knowledge levels is not well understood.

研究 の 目的:

• To evaluate the performance of medical students with and without formal pharmacology knowledge using AI-LLM GPTs, internet search engines, e-books, or self-knowledge for multiple-choice questions (MCQs).

主な方法:

• A cross-sectional study involved 100 medical students (50 naive, 50 learned) at a tertiary care hospital.; Participants answered MCQs using self-knowledge, e-books, Google, or ChatGPT-4o.; Scores were compared using analysis of covariance, with self-knowledge as a covariate.

主要な成果:

• Learned students outperformed naive students across all methods (P<.001), with the greatest effect size for AI-LLM GPTs.; Performance hierarchy for all students: AI-LLM GPT > internet search engine > self-knowledge ≈ e-books.; Naive students using AI scored higher than learned students using Google or e-books (P<.01).

結論:

• AI-LLM GPTs enhance MCQ performance, especially for students with limited prior knowledge.; AI tools can enable less knowledgeable students to outperform peers using traditional resources.; Further research is needed on AI's impact on deep learning and critical thinking in medical education.