Title: Evaluation method of teaching reform quality in colleges and universities based on big data analysis

Authors: Xiumin Wang

Addresses: College of Information and Electronics Engineering, Shangqiu Institute of Technology, Shangqiu, 476000, Henan, China

Abstract: Research on the quality evaluation of teaching reforms plays an important role in promoting improvements in teaching quality. Therefore, an evaluation method of teaching reform quality in colleges and universities based on big data analysis is proposed. A multivariate logistic model is used to select the evaluation indicators for the quality evaluation of teaching reforms in universities. And clustering and cleaning of the evaluation indicator data are performed through big data analysis. The evaluation indicator data is used as input vectors, and the results of the teaching reform quality evaluation are used as output vectors. A support vector machine model based on the whale algorithm is built to obtain the relevant evaluation results. Experimental results show that the proposed method achieves a minimum recall rate of 98.7% for evaluation indicator data, the minimum data processing time of 96.3 ms, the accuracy rate consistently above 97.1%.

Keywords: big data analysis; colleges and universities; reform quality evaluation; multivariate logistic model; whale algorithm; support vector machine model.

DOI: 10.1504/IJBIDM.2024.140881

International Journal of Business Intelligence and Data Mining, 2024 Vol.25 No.3/4, pp.306 - 322

Received: 10 Aug 2023
Accepted: 16 Nov 2023
Published online: 03 Sep 2024 *

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