Fuzzy Evaluation Model of Teaching Quality of Physical Education Course Based on Deep Reinforcement Learning

• Published in: Multimedia Technology and Enhanced Learning Vol. 446; pp. 140 - 152
• Main Authors: Wang, Zhiqiang, Xu, Xiangyu
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer 2022; Springer Nature Switzerland
• Series: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
• Subjects: Bartlett sphere test; Deep reinforcement learning; Factor analysis; Fuzzy evaluation; K-Mean clustering; Physical education courses; Teaching quality
• ISBN: 3031181220; 9783031181221
• ISSN: 1867-8211; 1867-822X
• DOI: 10.1007/978-3-031-18123-8_11

Because there are many factors affecting teaching evaluation, the evaluation results are difficult to reach a high level. Therefore, a fuzzy evaluation model of teaching quality of physical education course based on deep reinforcement learning is designed. On the basis of clarifying the requirements of teaching quality evaluation, the factor analysis method is used to preprocess the teaching data, the Bartlett spherical test is used to verify it, and the data meeting the verification requirements are K-mean clustered. Finally, based on the clustered data results, the fuzzy evaluation model is constructed according to the idea of minimum membership weighted average deviation. The test results show that the evaluation results of the design model have high adaptability with the actual results, and can meet the evaluation needs.