Research on the Application of the "PBL-AI-Traditional Teaching" Trinity Teaching Model in Clinical Medicine Theory and Practice Teaching
Description
Background: This study aims to evaluate the role and efficiency of the "PBL-AI-Traditional Teaching" integrated teaching model in clinical medical theory and practice teaching, in order to make up for the shortcomings of a single teaching method and enhance students' comprehensive abilities. Method: From September 2018 to September 2023, a prospective recruitment of 160 first-year clinical medicine students was conducted. Randomly assign participants to the "PBL-AI-Traditional Teaching" group and the traditional teaching group, and implement different teaching plans separately. Evaluate students' various performances and analyze their various self perception abilities through pre - and post class quizzes and anonymous questionnaire surveys. Result: The research results showed that the PBL-AI-traditional teaching group was significantly better than the traditional teaching group in terms of skill total score, theoretical total score, basic mastery, humanities mastery, prevention mastery, and clinical mastery (P<0.001), especially in clinical fields such as internal medicine and surgery. In addition, students in the PBL-AI-traditional teaching group scored significantly higher than those in the traditional teaching group in terms of learning motivation, comprehension ability, teacher-student interaction, communication ability, clinical thinking ability, self-learning ability, teamwork ability, and knowledge absorption ability (P<0.001). At the same time, the survey score of PBL-AI-traditional teaching group students' free time consumption was significantly lower than that of the traditional group (P<0.001). Conclusion: The PBL-AI-traditional teaching model is an effective method for improving students' comprehensive skills, basic knowledge, and clinical application abilities, and can effectively promote students' active learning and practical abilities.
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Research Design and Participants Research Design: This study adopts a prospective, randomized controlled design to divide first-year clinical medicine students at Qilu Medical College into a "PBL AI Traditional Teaching" group and a traditional teaching group. Participants: The research subjects are first-year clinical medicine students who enrolled between September 2018 and September 2023, totaling 160 people. Among them, 78 people were assigned to the "PBL AI Traditional Teaching" group and 82 people were assigned to the traditional teaching group. method: PBL AI Traditional Teaching Group: Combining PBL, AI assisted, and traditional teaching. Before class, students watch videos, read materials, and complete quizzes; In class, group discussions and case analysis are conducted using AI technology; Complete quizzes and questionnaires after class. Traditional teaching group: adopting traditional lecture style teaching, simple pre class preparation, and completing the same tests and questionnaires after class. Data collection: Test: Both groups of students participate in the licensed physician qualification exam, which consists of two parts: skill analysis and basic theory. We collected the scores of students participating in the practicing physician qualification examination and compared the results generated by each group using independent sample t-test. Questionnaire: Evaluate students' views on the teaching mode after class, including learning motivation, comprehension ability, etc. Preparation time: Record students' preparation time before class. Data analysis: Perform independent sample t-test and chi square test using IBM SPSS Statistics 25, with a significance level of α=0.05. The reliability of the questionnaire was evaluated using the Cronbach alpha coefficient (α=0.872). Instruments and software: AI technology: using AI big language models (such as ChatGPT) to assist learning. Statistical analysis software: IBM SPSS Statistics 25。 workflow Pre class preparation: The teacher prepares lecture videos, supplementary materials, and test questions, and students complete pre class learning and testing as required. Classroom teaching: Teachers guide students to conduct case analysis, group discussions, and PPT presentations, combined with AI technology for interactive learning. Post class assessment: Students complete post class quizzes and questionnaire surveys, and teachers summarize and review classroom content. Data organization and analysis: Collect test and questionnaire data, conduct statistical analysis, and compare the performance and satisfaction of two groups of students.