Abstract

Abstract The flaws in the conventional teaching quality evaluation system that have always existed have not been fixed since the start of the new century. This study suggests a teaching assessment model for college education that utilizes the CIPP model since there is a pressing need for a model that can satisfy the demands of the modern educational environment. The investigation examines the relevance of both approaches to teaching quality evaluation in educational institutions by combining the advantages of CIPP and BP neural networks. The artificial neural network’s working mechanism is described, the weights within the BP learning algorithm are modified, and the first version of the teaching assessment model is inferred based on an analysis of the structure and function of neurons. The conceptual model of teaching quality assessment in higher education is intended to be completed by the model’s algorithm and framework. Investigate and analyze the teaching quality of S colleges and universities using the empirical analysis approach. The results of the empirical investigation show that the correlation coefficients of the 4 dimensions of teaching evaluation are above 0.6, with control between 0.3-0.8, and they have a strong correlation. The Cronbach’s alpha coefficients of the survey are all above 0.7, with very good reliability.

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