Research and Analysis on the Evaluation of University Fusion System Based on Dynamic Group Strategy Teaching Optimization Algorithm

Abstract

Dynamic group strategy teaching optimization algorithm can simulate the natural evolution process to find the optimal teaching mix. This study uses the algorithm to constantly iterate the process characteristics to generate a new teaching strategy mix, and carries out an application analysis on the teaching mix. 662 students from 5 universities are tested by scale s. The process of S PPS is used to analyze and evaluate the recovered data. The results show that the algorithm can effectively improve the overall quality of talent training, and provide a reference direction for constructing a multi-dimensional integrated education model and exploring a new path for students' all-round development.