Exploration of the “Digital Intelligence+Group Learning”  Model in Molecular Biology Teaching

doi:10.3870/j.issn.1672-8009.2026.03.018

Journal of Medical Molecular Biology ›› 2026, Vol. 23 ›› Issue (3): 361-366.doi: 10.3870/j.issn.1672-8009.2026.03.018

• Medical Education • Previous Articles Next Articles

Exploration of the “Digital Intelligence+Group Learning” Model in Molecular Biology Teaching

WANG Qinhao¹, SUN Mao¹, YANG Guodong¹, LIU Zidong², ZHAO Jing¹

¹Department of Biochemistry and Molecular Biology,²Office of Teaching and Research,School of Basic Medical,Air Force Medical University,Xi’an,710032

Received:2025-10-20 Published:2026-06-01
Contact: ZHAO Jing(E-mail:zhaojing@fmmu.edu.cn)
Supported by:
National Natural Science Foundation of China(No.82472908),Program on Medical Education by Chinese Medical Association(No.2025B155),the Teaching Research Project at the Air Force Medical University(No.2024YB08),Teaching Project of the School of Basic Medical Sciences of Air Force Medical University(No.2024-JCJXKT-YB-01,No.2024-JCJXKT-YB-07,No.2025-JCJXKT-YB-12),Air Force Medical University Smart Courses(No.ZHKC2025001)

Abstract

Abstract: Objective To explore the application effect of the “Digital Intelligence+Group Learning” model in molecular biology teaching,in order to address the challenges of traditional teaching in personalized support and the cultivation of high-order abilities. Methods A total of 750 five-year undergraduate students were selected and divided into an experimental group(adopting Digital Intelligence+Group Learning)and a control group(adopting traditional lecture-based teaching).A mixed research method was used for evaluation. Results The experimental group performed significantly better than the control group in formative assessment(92.6±6.2 vs 85.4±8.7)and summative assessment(85.5±8.2 vs 80.3±9.1)(P<0.01),and also demonstrated better performance in knowledge integration,case analysis,and learning interest. Conclusion This model may effectively compensate for the deficiencies of traditional teaching to a certain extent,enhance students’ comprehensive abilities,and provide practical references for medical education reform.

Key words: digital intelligence technology, group learning, molecular biology, teaching reform

CLC Number:

G642

WANG Qinhao, SUN Mao, YANG Guodong, LIU Zidong, ZHAO Jing. Exploration of the “Digital Intelligence+Group Learning” Model in Molecular Biology Teaching[J]. Journal of Medical Molecular Biology, 2026, 23(3): 361-366.

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Exploration of the “Digital Intelligence+Group Learning” Model in Molecular Biology Teaching

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