Abstract: Through the integration of information technology, smart classrooms have improved the efficiency of teaching interaction and resource management. However, how to effectively utilize this data for learning path tracking and evaluation is still an urgent problem to be solved. Based on big data analysis technology, this article designs and implements a smart classroom learning path tracking system, which includes functional modules such as learning path collection and tracking, real-time monitoring and feedback, learning behavior analysis and visualization. Through methods such as data mining and pattern recognition, time series analysis and prediction, this article conducts in-depth analysis of student learning paths in smart classrooms to evaluate learning behavior and effectiveness. Through case analysis, the effectiveness of the system was verified, aiming to provide a feasible solution for personalized learning path design and teaching effectiveness evaluation in a smart classroom environment.

Key words: Big data analysis, Smart classroom, Learning path tracking, Real time monitoring, Analysis of learning behavior, “Zhixue cloud platform”