Academic evaluation is an important factor in promoting teaching reform, which can provide data assist for teaching reform and improve learning methods. At present, academic evaluation research mainly focuses on building a single model for evaluation, and the evaluation method is single. The academic evaluation method based on multiple regression analysis utilizes the advantages of different regression analysis methods in data processing to improve the accuracy of academic evaluation. Gaussian model analysis, partial least squares regression, and pluralistic linear algorithm were effectively integrated. The performance and efficiency of methods were tested through real sample from four majors in applied chemistry major, Language related humanities majors, accounting, and computer science major in universities. The verification results indicate that the academic evaluation algorithm has very high accuracy and stability, and can provide data support for improving teaching quality.
Yao et al. (Thu,) studied this question.