The role of generative AI tools in case-based learning and teaching evaluation of medical biochemistry.

Journal: BMC medical education
Published Date: Aug 22, 2025

Abstract

BACKGROUND: Medical biochemistry, a fundamental course in medical education, has a complex and expanding knowledge base. Traditional teaching methods often fail to meet students' needs for in-depth understanding and personalized learning. Students can become overwhelmed by the vast array of biochemical concepts, reactions, and molecular structures.

Authors

  • Liang Li
    School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China.
  • Weiwei Zhang
    Department of Laboratory Medicine, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.
  • Kun Zhang
    Philosophy Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
  • Yuhan Yang
    West China School of Medicine, Sichuan University, No.17 People's South Road, Chengdu, 610041, Sichuan, China. Electronic address: yyh_1023@163.com.
  • Lan Wang
    The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Luo Zuo
    Department of Gastroenterology, the Second Affiliated Hospital of Chengdu Medical College, Chengdu, 610057, China.
  • Yiran Sun
    Department of pharmacology, School of Pharmacy, Chengdu Medical College, 783 # Xindu Avenue, Chengdu, 610500, China. 18202863885@163.com.
  • Quekun Peng
    Department of Biochemistry and Molecular Biology, School of Biosciences and Technology, Chengdu Medical College, 783 # Xindu Avenue, Chengdu, 610500, China. pengquekun@cmc.edu.cn.

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