Research on The Construction and Efficiency Evaluation Index System of The Teaching Management System of Computers Science-Based Applied Talent Training Practice in Colleges and Universities

This study aims to construct a Teaching Management System (TMS) and develop an efficiency evaluation index system for computer science-based applied talent training in higher education institutions. The TMS integrates advanced technologies such as artificial intelligence (AI) and machine learning (ML) to enhance teaching and learning processes. Through requirement analysis, modular design, and agile development practices, the system is built to meet the specific needs of computer science education. The efficiency evaluation index system covers multiple dimensions, including system functionality, user satisfaction, teaching effectiveness, and data management. Using the Ana-lytic Hierarchy Process (AHP), weights are assigned to each indicator to provide a comprehensive assessment framework. Empirical data from participating universities validate the model and offer insights for system improvements. The results show that the TMS significantly improves the efficiency and quality of educational delivery, while the evaluation framework provides a scientific basis for continuous enhancement. Future work will focus on expanding the application scope, refining the evaluation system, and exploring further technological integrations to continuously improve teaching management and student learning outcomes.