A Research-Oriented Teaching Model for Public Physical Education in Colleges Based on Extenics Theory

Lin, Wang; Deng, Weifeng

doi:10.3991/ijet.v16i01.19719

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…There are 8 identical and 4 different. It can be seen that the important indicators selected from different angles basically overlap [ 8 ], but there are also a small number of indicators that are different due to different evaluators' cognitive laws and reference angles. In this paper, the results of the two methods are combined, and the same 8 indicators are used as the input of the next neural network evaluation model.…”

Section: Evaluation Of Wireless Sensor Technologymentioning

confidence: 99%

Wireless Sensor Technology-Based Physical Education Teaching Evaluation

Feng

2022

Computational Intelligence and Neuroscience

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A wireless sensor network (WSN) is a group of geographically scattered and specialized sensors to monitor and record variables related to environmental and storing the obtained data in a vital location. These networks have applications and can be utilized in different research domains including physical education where error prediction is assumed as one of the core issues. Thus, careful attention is required from the researcher to provide reliable and accurate prediction models. Thus, aiming the shortage of large prediction error in the physical education evaluation, which is based on the BP neural network and wireless sensor technology, a combination of AFP and questionnaire survey method is proposed in order to improve the accuracy and predictability of evaluation, according to the characteristics of different evaluation subjects. We select the evaluation index system as the input of wireless sensor technology and then use the principle of genetic algorithm to select the optimal individual and optimize the initial parameters of wireless sensor technology to establish the evaluation model of physical education quality. Through the training and testing of sample data, it is shown that the model greatly improves the accuracy of physical education quality evaluation and has a good application prospect in physical education evaluation.

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Section: Evaluation Of Wireless Sensor Technologymentioning

confidence: 99%

Wireless Sensor Technology-Based Physical Education Teaching Evaluation

Feng

2022

Computational Intelligence and Neuroscience

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“…After experiencing the trough, artificial intelligence has now entered a new stage. As humans demand for intelligent applications in the future, more uses of artificial intelligence will be introduced to humans [24]. Table 1 is the policy documents and main content related to artificial intelligence.…”

Section: Methods Of Practicability Of Sports Goods In the Sports Fiel...mentioning

confidence: 99%

Practicability of Sports Goods in the Sports Field Based on Artificial Intelligence Technology

Zhang

Jianghua

2022

Mobile Information Systems

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People are in the intellectual age. The use of technologies such as smart search engines, machine translation, fingerprint analysis, facial scanning, and self-driving makes people’s social and work lives happier. The intersection of artificial intelligence and other projects has also become the focus of research in the new era. This article uses comparative experimental methods and sampling methods, puts forward the evaluation method of association rules in the recommendation of sports goods, and compares the selection of sensors used by the five types of sports companies in the sports experiments. In the experiment part, according to the minimum confidence level, the two rules are met. Minimum confidence is a threshold defined by users or experts to measure confidence, which represents the lowest reliability of association rules. The conclusion is that 30% of users have bought running shoes and hiking shoes at the same time and 66.6% of users have also purchased sports suits; there are also sports suits purchased at the same time. All mountain bike users have bought sports gloves. The weight of Freescale is 0.2530, the weight of Bosch is 0.4457, the weight of ST is 0.0946, the weight of VTI is 0.0953, and the weight of Konix is 0.1114. The experimental results show that the selection result of the three-axis acceleration sensor is the SMB380 model of Bosch.

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“…Wang, L. et al designed the ROT teaching model in order to continue the public physical education teaching model in colleges and universities. At the same time, in order to extend the model realization effect, the model was improved by using EIS, which enhanced the extension effect of the model and improved the physical education teaching model in colleges and universities [11]. Zhang, N. et al argued that the integration of the physical education model with technological culture could enhance the understanding of physical education and cultural preservation.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Application of Traditional Sports Culture in College Physical Education Teaching under the Background of Deep Learning

Meng,

2023

Applied Mathematics and Nonlinear Sciences

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In this paper, the transformer target detection algorithm is established by combining deep learning technology, and the Deep algorithm is added on the basis of SORT to optimize and improve SORT and overcome the problems of SORT. After the DeepSORT model is constructed, YOLOv5 is introduced into the model, and finally, the YOLOv5-DeepSORT model for sports element detection and tracking is constructed and completed. The ATT-BERT sports culture element entity recognition model is constructed from four levels: the BERT layer, the BiLSTM layer, the attention layer, and the CRF layer, which results in an application framework for the integration of traditional sports culture into teaching. The influence factors of sports culture perception and sports teaching, as well as the integration of traditional ethnic sports culture into sports teaching in Z, were empirically examined. The study shows that the correlation coefficient between the two is around 0.465, and there is a positive and strong correlation between the two. The correlation coefficients of the dimensions for physical education students and non-physical education students were 0.513, 0.483, 0.485, and 0.462, respectively. The most common teaching methods used by teachers in physical education classrooms integrating traditional sports culture were explanation, demonstration, and complete decomposition, with ratios of 0.78 and 0.7, respectively. The integration of sports culture into physical education has resulted in good results. The outcome was satisfactory.

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A Research-Oriented Teaching Model for Public Physical Education in Colleges Based on Extenics Theory

Cited by 9 publications

References 14 publications

Wireless Sensor Technology-Based Physical Education Teaching Evaluation

Wireless Sensor Technology-Based Physical Education Teaching Evaluation

Practicability of Sports Goods in the Sports Field Based on Artificial Intelligence Technology

Research on the Application of Traditional Sports Culture in College Physical Education Teaching under the Background of Deep Learning

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