本研究聚焦面向学情分析的面部表情识别情感分析系统V1.0，围绕技术可行性论证—表情分类提取—实践应用验证展开研究，通过改进深度神经网络模型提升表情识别精度，采集过程性表情数据支撑学情分析，最终通过教师认可调查与学生体验反馈优化系统，实现技术研究—教学应用的融合。

This study focuses on the Facial Expression Recognition and Sentiment Analysis System V1.0 for learning situation analysis. It unfolds around the research of technical feasibility demonstration, expression classification extraction, and practical application verification. By improving the deep neural network model to enhance the accuracy of expression recognition, collecting procedural expression data to support learning situation analysis, and ultimately optimizing the system through teacher recognition surveys and student experience feedback, the study achieves the integration of technical research and teaching application.