Wang, Peipei (2023) Evaluation and analysis of effectiveness and training process quality based on an interpretable optimization algorithm: The case study of teaching and learning plan in taekwondo sport. Applied Artificial Intelligence, 37 (1). ISSN 0883-9514
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Abstract
Taekwondo is a martial art emphasizing defense, protection, and moral and spiritual values. Evaluating the effectiveness and quality of Taekwondo sports training is a complex task that requires the consideration of various factors, such as the learners’ skills, physical condition, and psychological state. Traditional methods for evaluating sports training effectiveness and quality have limitations, such as being subjective, time-consuming, and not considering individual differences. This paper proposes a new approach to evaluating the effectiveness and quality of Taekwondo sports training using optimization algorithms. Specifically, three optimization algorithms, TLBO, DSLTLBO, and GWO, are compared and analyzed for their suitability at different levels. These algorithms can automatically adjust the sports training plan based on individual differences and learner feedback, which can address the limitations of traditional evaluation methods. Validity statistics and moral/spiritual level assessment are used to evaluate the training results and process quality. The results indicate that different optimization algorithms are appropriate for learners at different levels. Diversified algorithm forms are recommended for a comprehensive evaluation of the sports plan. This paper provides insights into optimizing Taekwondo sports training and highlights the importance of cultivating moral and spiritual values through this martial art. The proposed approach can potentially improve the effectiveness and quality of Taekwondo sports training and can be extended to other sports or physical activities.
Item Type: | Article |
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Subjects: | AP Academic Press > Computer Science |
Depositing User: | Unnamed user with email support@apacademicpress.com |
Date Deposited: | 12 Jun 2023 04:49 |
Last Modified: | 20 Sep 2024 03:53 |
URI: | http://info.openarchivespress.com/id/eprint/1512 |