Research Article
Fuzzy Evaluation Model of Teaching Quality of Physical Education Course Based on Deep Reinforcement Learning
@INPROCEEDINGS{10.1007/978-3-031-18123-8_11, author={Zhiqiang Wang and Xiangyu Xu}, title={Fuzzy Evaluation Model of Teaching Quality of Physical Education Course Based on Deep Reinforcement Learning}, proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings}, proceedings_a={ICMTEL}, year={2022}, month={10}, keywords={Deep reinforcement learning Physical education courses Teaching quality Fuzzy evaluation Factor analysis Bartlett sphere test K-Mean clustering}, doi={10.1007/978-3-031-18123-8_11} }- Zhiqiang Wang
Xiangyu Xu
Year: 2022
Fuzzy Evaluation Model of Teaching Quality of Physical Education Course Based on Deep Reinforcement Learning
ICMTEL
Springer
DOI: 10.1007/978-3-031-18123-8_11
Abstract
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.
