Construction of Teaching Quality Assessment Model Combined with Data Mining Algorithm

Whether a reasonable and objective scientific assessment can be made for the teaching quality of teachers is of great research significance in promoting the overall improvement of teaching quality. In this paper, the Apriori association rule mining algorithm is utilized to mine the association rules on the subject teaching quality assessment samples, and the support and confidence range of the results obtained are between 0.0836∼0.1567 and 0.3148∼0.3874 respectively, and the model has the ability of effective mining. Based on the PCA teaching quality assessment model, the covariance matrix and eigenvalues were calculated sequentially to complete the selection of principal components of teaching quality assessment, and the principal component loadings and scores were obtained. From the result of component matrix operation, the final result score of teaching quality assessment of the subject course is 8.3145, which can realize the quantitative assessment of teaching quality. Applying the model in practice, the teaching quality assessment results show that the top 5 dimensions of the teaching quality assessment score are proper course progress, on-time starting and stopping, student interaction, highlighting the key points, and neatness of the board, and the average value of the scores is more than 2 points.