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Personalized Physical Education Teaching Path Planning and Optimization Based on Deep Reinforcement Learning

  
11 nov. 2024
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Da-Wei, C., Chao, L., Shun, W., Xun-Ling, W., & Wen-fang, W. (2018). Research and application of multimedia digital platform in the teaching of college physical education course. Journal of Intelligent & Fuzzy Systems, 34(2), 893-901. Search in Google Scholar

Lee, H. S., & Lee, J. (2021). Applying artificial intelligence in physical education and future perspectives. Sustainability, 13(1), 351. Search in Google Scholar

Vilchez, J. A., Kruse, J., Puffer, M., & Dudovitz, R. N. (2021). Teachers and school health leaders’ perspectives on distance learning physical education during the COVID‐19 pandemic. Journal of School Health, 91(7), 541-549. Search in Google Scholar

Antonova, A., & Dankov, Y. (2022). Smart services in education: facilitating teachers to deliver personalized learning experiences. In Proceedings of the Computational Methods in Systems and Software (pp. 108-117). Cham: Springer International Publishing. Search in Google Scholar

Bernacki, M. L., Greene, M. J., & Lobczowski, N. G. (2021). A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose (s)?. Educational Psychology Review, 33(4), 1675-1715. Search in Google Scholar

Xu, M., Zhai, Y., Guo, Y., Lv, P., Li, Y., Wang, M., & Zhou, B. (2019). Personalized training through Kinect-based games for physical education. Journal of Visual Communication and Image Representation, 62, 394-401. Search in Google Scholar

Zhang, Z., & Cai, J. (2022, May). Research on personalized sports training methods from the perspective of data analysis. In International Symposium on Computer Applications and Information Systems (ISCAIS 2022) (Vol. 12250, pp. 144-149). SPIE. Search in Google Scholar

Dijkhuis, T. B., Blaauw, F. J., Van Ittersum, M. W., Velthuijsen, H., & Aiello, M. (2018). Personalized physical activity coaching: a machine learning approach. Sensors, 18(2), 623. Search in Google Scholar

Kwon, E. H., & Block, M. E. (2017). Implementing the adapted physical education E-learning program into physical education teacher education program. Research in developmental disabilities, 69, 18-29. Search in Google Scholar

Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational research review, 31, 100339. Search in Google Scholar

Liu, T. (2022). Personalized recommendation method of sports online video teaching resources based on multiuser characteristics. Mathematical Problems in Engineering, 2022(1), 5762505. Search in Google Scholar

Roure, C., & Pasco, D. (2022). Exploring the effects of a context personalization approach in physical education on students’ interests and perceived competence. Journal of Teaching in Physical Education, 42(2), 331-340. Search in Google Scholar

Liu, F. (2024). Design of intelligent assistive system for physical education: based on personalized training plan. Journal of Electrical Systems, 20(3s), 328-340. Search in Google Scholar

Kang, L. (2017, May). Research on the Application of Personalized Education in College Physical Education. In 2017 4th International Conference on Education, Management and Computing Technology (ICEMCT 2017) (pp. 390-393). Atlantis Press. Search in Google Scholar

Guryanov, M., Bocharin, I., Kalyuzhny, E., Kraynik, V., Limarenko, O., Lukashevich, E., ... & Tyupa, P. (2024). Personalization of physical education based on the study of body composition and body vegetative support in female students. Journal of Physical Education and Sport, 24(2), 353-359. Search in Google Scholar

Hou, X., Fang, D., & Guo, J. (2024). Research on personalized path recommendation of college physical education online teaching based on improved particle swarm optimization. Revista multidisciplinar de las Ciencias del Deporte, 24(94). Search in Google Scholar

Verret, C., Roure, C., Ouellet, C., Massé, L., Grenier, J., & Bergeron, G. (2022). Situational interest of students with autism spectrum disorder using context personalization in physical education. European Journal of Adapted Physical Activity, 15. Search in Google Scholar

Juditya, S., Suherman, A., Ma’mun, A., & Rusdiana, A. (2019). Personalized system of instruction (psi) models: using digital teaching materials on learning. International Journal of Innovation, Creativity and Change, 9(5), 214-324. Search in Google Scholar

Gurieva, N., Guryev, I., Pacheco Sánchez, R., & Salazar Martínez, E. (2019). Augmented reality for personalized learning technique: Climbing gym case study. Open J. Inf. Technol, 2, 21-34. Search in Google Scholar

Bishop, P. A., Downes, J. M., Netcoh, S., Farber, K., DeMink-Carthew, J., Brown, T., & Mark, R. (2020). Teacher roles in personalized learning environments. The Elementary School Journal, 121(2), 311-336. Search in Google Scholar

Alamri, H., Lowell, V., Watson, W., & Watson, S. L. (2020). Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation. Journal of Research on Technology in Education, 52(3), 322-352. Search in Google Scholar

Kaswan, K. S., Dhatterwal, J. S., & Ojha, R. P. (2024). AI in personalized learning. In Advances in Technological Innovations in Higher Education (pp. 103-117). CRC Press. Search in Google Scholar

Katsumata, M. (2020, August). A multiple smart device-based personalized learning environment. In 2020 IEEE 10th International Conference on Intelligent Systems (IS) (pp. 498-502). IEEE. Search in Google Scholar

Croce Federico,Valentini Riccardo,Maranghi Marianna,Grani Giorgio,Lenzerini Maurizio & Rosati Riccardo. (2024). Ontology-Based Data Preparation in Healthcare: The Case of the AMD-STITCH Project. SN Computer Science(4), Search in Google Scholar

Görne Lorenz,Reuss Hans Christian,Krätschmer Andreas & Sauerwald Ralf. (2022). Smart data preprocessing method for remote vehicle diagnostics to increase data compression efficiency. Automotive and Engine Technology(3-4),307-316. Search in Google Scholar

Jonas Elsborg & Arghya Bhowmik. (2024). ArtiSAN: navigating the complexity of material structures with deep reinforcement learning. Machine Learning: Science and Technology(3),035043-035043. Search in Google Scholar

Min Zhao & Junwen Lu. (2024). Energy-aware tasks offloading based on DQN in medical mobile devices. Journal of Cloud Computing(1),128-128. Search in Google Scholar