The performance evaluation of teaching reform based on hierarchical multi-task deep learning

Jianlei Zhang

International Journal of Information Technology and Management, 2024, vol. 23, issue 3/4, 318-329

Abstract: The research goal is to solve the problems of low accuracy and long time existing in traditional teaching reform performance evaluation methods, a performance evaluation method of teaching reform based on hierarchical multi-task deep learning is proposed. Under the principle of constructing the evaluation index system, the evaluation indicator system should be constructed. The weight of the evaluation index is calculated through the analytic hierarchy process, and the calculation result of the evaluation weight is taken as the model input sample. A hierarchical multi-task deep learning model for teaching reform performance evaluation is built, and the final teaching reform performance score is obtained. Through relevant experiments, it is proved that compared with the experimental comparison method, this method has the advantages of high evaluation accuracy and short time, and can be further applied in relevant fields.

Keywords: hierarchical multi-task deep learning; reform in education; performance evaluation; analytic hierarchy process; loss function. (search for similar items in EconPapers)
Date: 2024
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