Affiliation:
1. 1 Department of Physical Education , Guangdong Pharmaceutical University , Guangzhou , , China
Abstract
Abstract
Physical education curriculum in colleges and universities has been paid more and more attention and turned one of the important contents of education curriculum. In order to make up for the deficiency that traditional tests can only get a general score and further optimize the physical education curriculum, this study selected G-DINA model according to Wald statistic, analyzed the physical education curriculum textbooks, and clarified the cognitive attributes and hierarchical relations of the curriculum. Then, pursuant to the attributes and hierarchical relations obtained, this study constructed typical assessment model matrix and developed the curriculum cognitive diagnosis test paper based on Q matrix. Through comparing results of the two physical education curriculum diagnosis test papers based on G-DINA model, it can be seen that the ratio of students who master the attributes A4 and A5 is climbed up to 67.2% and 59%, respectively, which indicates that students’ overall mastery of A4 and A5 knowledge blocks has been significantly improved after teachers’ intensive and in-depth optimized teaching. Therefore, it can be concluded from the above that the optimized teaching of physical education courses in colleges and universities plays a significant role, and at the same time, for teachers, G-DINA model is conductive to fully controlling the teaching feedback effect, timely adjusting the teaching key and difficult points, and predicting the depth and breadth of teaching trend. Even further, the model is helpful for college physical education institutes to deepen the physical education curriculum optimization in colleges and universities.
Subject
Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science
Reference33 articles.
1. Dong, J,. Yu, H. W. (2020). Particle swarm optimization neural network for research on artificial intelligence college English classroom teaching framework. Journal of Intelligent and Fuzzy Systems, (4),1-13.
2. Kang, C., Shi, C., Liu, Z., et al. (2020). Research on the optimization of welding parameters in high-frequency induction welding pipeline. Journal of Manufacturing Processes, 59, 772-790.
3. Sun, Y., Gao, D., Zhang, Z., et al. (2022). Research on Air-Flow-Field Characteristics and Structural Optimization of the Guide Channels of the Autoclave. Energies, 15.
4. Cao, Q., Kang, W., Sajid, M. J., et al. (2021). Research on the optimization of carbon abatement efficiency in China on the basis of task allocation. Journal of Cleaner Production, 299(9), 126912.
5. Cai, S., Liu, W., Long, S., et al. (2021). Research on the mechanism of particle deposit effects and process optimization of nanosecond pulsed laser truing and dressing of materials. RSC Advances, 11.