Pathways to Improve the Effectiveness of Multidimensional Data Analysis in Decision Support for Instructional Management

In recent years, colleges and universities have been carrying out teaching management reforms and exploring new talent cultivation modes with the ‘Teaching Quality and Teaching Reform Project’. Research from the teaching management needs, the use of data for teaching management to provide decision support methods. This paper constructs a decision support system for teaching management and proposes improvements on the basis of the original C4.5 algorithm. Taking the data provided by some colleges of a university as an example, the statistical analysis mining method is used to analyse the text of students’ evaluation of teaching and derive the relationship between teachers’ basic information and teaching quality. On this basis, student data are collected to construct the final stage grade prediction model, and the performance of C4.5 algorithm before and after the improvement is evaluated through experiments, and the experimental results show that the accuracy of C4.5 algorithm in predicting passing grades can reach 93.43% after the improvement, and finally cluster analysis is carried out according to the students’ performance in school.