大学物理实验教学存在实验时间安排紧凑，学生在实验原理理解、操作要点掌握等方面存在困难，且教师无法对学生进行有效的个性化指导等问题.针对这些问题，本研究构建了人工智能体辅助系统以提升实验教学效果.在不同平台进行了AI智能体的建设，并对比分析差异，且以声光衍射及液体中声速测定实验验证其效果.实验设置对照组（传统教学）与实验组（智能体辅助）进行对比.实验数据显示实验组在高分段预习成绩较对照组提升12.2%；在实验操作阶段，AI智能体通过提供个性化指导，实验组在操作过程中的错误率明显低于对照组，且完成实验的时间平均缩短了约10%.本研究有关大学物理实验课程的AI智能体建设和智能体提升大学物理实验教学的探索，可为其他课程的AI智能体制作提供参考.

In college physics experiment teaching, issues such as tight scheduling of experiment time, students' having difficulties in comprehending experimental principles and mastering operational essentials, and teachers' inability to provide effective personalized guidance persist. To address these challenges, this study develops an artificial intelligence agent-assisted system to enhance experimental teaching effectiveness. The paper proposes AI agents across different platforms and conducted comparative analyses of their differences. The systems application effectiveness is based on acousto-optic diffraction experiments and sound velocity measurement in liquids. The experiment involves a control group (traditional teaching methods) and an experimental group (AI agent-assisted). Results show that in the high-score range (30-40 points), the experimental group shows a 12.2% improvement in pre-experiment quiz scores compared to the control group. During the experimental operation phase, the AI agent provides personalized guidance, resulting in significantly lower error rates and an average 10% reduction in experiment completion time for the experimental group. This research on AI agent development for university physics experiments and its exploration of enhancing experimental teaching through intelligent agents offers valuable references for AI agent development in other courses.