Exploring the Implementation Path of Artificial Intelligence-Enabled Pharmacology Classroom Teaching

人工智能(AI)技术为药理学课堂教学革新提供了新路径。本研究以建构主义理论为指导，探究AI赋能的个性化教学对学习目标达成的影响。实验组(n = 52)依托“超星学习通AI助教”平台，整合个性化学习路径、实时答疑及动态案例库功能；对照组(n = 52)采用传统教学。结果显示，AI组综合考核成绩(82.02 ± 6.691)显著高于对照组(78.42 ± 6.442) (p Artificial Intelligence (AI) technology offers innovative pathways for revolutionizing pharmacology classroom teaching. Guided by constructivist theory, this study explores the impact of AI-driven personalized teaching on learning objective attainment. The experimental group (n = 52) utilized the “Chaoxing Learning AI Tutor” platform integrating personalized learning paths, real-time Q&A, and dynamic case libraries, while the control group (n = 52) followed traditional methods. Results showed that the AI-enhanced group achieved significantly higher comprehensive scores (82.02 ± 6.691) than the control group (78.42 ± 6.442) (p < 0.01), with knowledge objective attainment reaching 80.8% and capability objective attainment improving to 0.79. Qualitative data indicated that 76.9% of students acknowledged the clinical relevance of dynamic case libraries, and 73.1% expressed satisfaction with personalized learning paths. However, classroom interaction (65.4%) and Q&A efficiency (69.2%) require further optimization. The study also addresses challenges such as technical adaptability and data privacy, proposing strategies to enhance AI integration. This research provides empirical evidence for AI applications in pharmacology education.