人工智能赋能CBCL模式对医学生临床决策能力及思政素养的影响研究OA

Objective To explore the impact of case-based collaborative learning(CBCL)mode empowered by artificial intelligence(AI)on the clinical decision-making ability and ideological and political literacy of medical students.Methods An embedded mixed methods research design was adopted.A total of 139 clinical medicine students were selected and divided into the experimental group(AI-CBCL,n=71)and the control group(traditional CBCL,n=68).A quasi-experimental controlled study was conducted in the teaching of the"circulatory system integrated course".Statisti-cal analyses were performed using independent samples t-test,chi-square test,and Cohen's d effect size.The teaching effectiveness was evaluated from multiple dimensions,including comprehensive grades,clinical decision-making ability,expert evaluation of classroom performance,and question-naire surveys.Results The experimental group showed significantly better knowledge mastery scores[(89.55±4.49)vs.(80.53±4.73),P<0.001]and clinical decision-making abilities[(105.97±6.50)vs.(93.63±6.35),P<0.001]compared with the control group.Experts'evaluations show that the ex-perimental group performed better than the control group in terms of ideological and political literacy,clinical thinking,and other dimensions of classroom performance(all P<0.01).Conclusion The AI-CBCL teaching mode effectively enhances students'clinical decision-making ability through three mechanisms:intelligent case generation,real-time decision support,and process evaluation feedback.It also integrates ideological and political education into professional teaching in an intelligent and con-textualized manner,achieving the coordinated development of knowledge,ability,and literacy,and providing a practical paradigm for the digital transformation of medical education.