Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology
Students love basketball, but traditional teaching approaches are no longer able to suit their demands. In this article, artificial intelligence is combined with innovative teaching methods to create a new type of learning. Firstly, under the SPOC teaching mode, intelligent sensors are used to colle...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
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| Online Access: | https://doi.org/10.2478/amns.2023.2.01578 |
| _version_ | 1797340540359933952 |
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| author | Yan Duoduo |
| author_facet | Yan Duoduo |
| author_sort | Yan Duoduo |
| collection | DOAJ |
| description | Students love basketball, but traditional teaching approaches are no longer able to suit their demands. In this article, artificial intelligence is combined with innovative teaching methods to create a new type of learning. Firstly, under the SPOC teaching mode, intelligent sensors are used to collect basketball sports data, and Kalman filtering is used for processing and segmentation. Then, through the definition of basketball sports gesture, the data division of basketball sports gesture, designing the basketball sports gesture feature extraction method based on unit division, and using the SVM method to analyze the basketball sports gesture features, designing intelligent SPOC hybrid basketball teaching. Finally, the experiments on data collection and motion attitude resolution in basketball are designed to investigate the effects of intelligent SPOC hybrid basketball teaching. The results show that the deviations of the collected acceleration and angular velocity are within 10−2 orders of magnitude and 1.8°/s deviation, respectively, and the average recognition effect of various basketball postures is 0.925, which is able to effectively carry out basketball motion recognition. The experimental class 1’s physical quality improved by roughly seven after the teaching application was implemented, and the P-value for the improvement of different basketball sports was less than 0.05, indicating that the planned instruction can greatly enhance students’ physical quality and basketball abilities. |
| first_indexed | 2024-03-08T10:04:33Z |
| format | Article |
| id | doaj.art-460c31fb30844e8aa28732846c8644e2 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:04:33Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-460c31fb30844e8aa28732846c8644e22024-01-29T08:52:44ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01578Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence TechnologyYan Duoduo01College of Sports, Henan University of Technology, Zhengzhou, Henan, 450000, China.Students love basketball, but traditional teaching approaches are no longer able to suit their demands. In this article, artificial intelligence is combined with innovative teaching methods to create a new type of learning. Firstly, under the SPOC teaching mode, intelligent sensors are used to collect basketball sports data, and Kalman filtering is used for processing and segmentation. Then, through the definition of basketball sports gesture, the data division of basketball sports gesture, designing the basketball sports gesture feature extraction method based on unit division, and using the SVM method to analyze the basketball sports gesture features, designing intelligent SPOC hybrid basketball teaching. Finally, the experiments on data collection and motion attitude resolution in basketball are designed to investigate the effects of intelligent SPOC hybrid basketball teaching. The results show that the deviations of the collected acceleration and angular velocity are within 10−2 orders of magnitude and 1.8°/s deviation, respectively, and the average recognition effect of various basketball postures is 0.925, which is able to effectively carry out basketball motion recognition. The experimental class 1’s physical quality improved by roughly seven after the teaching application was implemented, and the P-value for the improvement of different basketball sports was less than 0.05, indicating that the planned instruction can greatly enhance students’ physical quality and basketball abilities.https://doi.org/10.2478/amns.2023.2.01578smart sensorkalman filterfeature extractionsvmspoc hybrid teaching68t01 |
| spellingShingle | Yan Duoduo Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology Applied Mathematics and Nonlinear Sciences smart sensor kalman filter feature extraction svm spoc hybrid teaching 68t01 |
| title | Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology |
| title_full | Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology |
| title_fullStr | Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology |
| title_full_unstemmed | Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology |
| title_short | Design and Application of SPOC Hybrid Teaching for College Basketball Teaching Based on Artificial Intelligence Technology |
| title_sort | design and application of spoc hybrid teaching for college basketball teaching based on artificial intelligence technology |
| topic | smart sensor kalman filter feature extraction svm spoc hybrid teaching 68t01 |
| url | https://doi.org/10.2478/amns.2023.2.01578 |
| work_keys_str_mv | AT yanduoduo designandapplicationofspochybridteachingforcollegebasketballteachingbasedonartificialintelligencetechnology |