Artificial intelligence-supported physical education during the pandemic: a physical skill auto-assessment and feedback approach based on a reflection-promoting mechanism.
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| Title: | Artificial intelligence-supported physical education during the pandemic: a physical skill auto-assessment and feedback approach based on a reflection-promoting mechanism. |
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| Authors: | Hsia, Lu-Ho (AUTHOR), Hwang, Gwo-Jen (AUTHOR), Lin, Yen-Nan (AUTHOR), Hwang, Jan-Pan (AUTHOR) |
| Source: | Educational Technology Research & Development. Jun2025, Vol. 73 Issue 3, p1429-1450. 22p. |
| Subjects: | Physical education, COVID-19, Reflective learning, Feedback control systems, Distance education, Yoga techniques, Artificial intelligence, Self-evaluation |
| Abstract: | In most physical education courses, teachers generally observe and interact with students face-to-face, so as to assess their learning status and provide immediate and appropriate guidance. However, during the COVID-19 pandemic, practical physical education courses moved completely online. Without physical contact, the safety, assessment, and overall learning quality of students in online physical education courses have become a difficult issue for teachers. Hence, the present study referred to the concept of reflective practice and developed a yoga skill auto-assessment and feedback (Auto-Yoga) system. It was implemented to provide students with instant professional evaluation and feedback, as well as to support the distance teaching of physical education courses. In order to verify the learning effects of the Auto-Yoga system, a class of 45 students was assigned to be the experimental group who adopted the Auto-Yoga system for learning, while the other class of 43 students as the control group adopted the conventional yoga skill learning (C-Yoga) system for learning during the period when face-to-face classes were not feasible due to the pandemic. The results showed that the Auto-Yoga system could significantly enhance students' yoga skill performance, learning motivation, and critical thinking. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 186781782 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Artificial intelligence-supported physical education during the pandemic: a physical skill auto-assessment and feedback approach based on a reflection-promoting mechanism. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hsia%2C+Lu-Ho%22">Hsia, Lu-Ho</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hwang%2C+Gwo-Jen%22">Hwang, Gwo-Jen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lin%2C+Yen-Nan%22">Lin, Yen-Nan</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hwang%2C+Jan-Pan%22">Hwang, Jan-Pan</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Educational+Technology+Research+%26+Development%22">Educational Technology Research & Development</searchLink>. Jun2025, Vol. 73 Issue 3, p1429-1450. 22p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Physical+education%22">Physical education</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Reflective+learning%22">Reflective learning</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+systems%22">Feedback control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Distance+education%22">Distance education</searchLink><br /><searchLink fieldCode="DE" term="%22Yoga+techniques%22">Yoga techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Self-evaluation%22">Self-evaluation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In most physical education courses, teachers generally observe and interact with students face-to-face, so as to assess their learning status and provide immediate and appropriate guidance. However, during the COVID-19 pandemic, practical physical education courses moved completely online. Without physical contact, the safety, assessment, and overall learning quality of students in online physical education courses have become a difficult issue for teachers. Hence, the present study referred to the concept of reflective practice and developed a yoga skill auto-assessment and feedback (Auto-Yoga) system. It was implemented to provide students with instant professional evaluation and feedback, as well as to support the distance teaching of physical education courses. In order to verify the learning effects of the Auto-Yoga system, a class of 45 students was assigned to be the experimental group who adopted the Auto-Yoga system for learning, while the other class of 43 students as the control group adopted the conventional yoga skill learning (C-Yoga) system for learning during the period when face-to-face classes were not feasible due to the pandemic. The results showed that the Auto-Yoga system could significantly enhance students' yoga skill performance, learning motivation, and critical thinking. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11423-025-10452-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 1429 Subjects: – SubjectFull: Physical education Type: general – SubjectFull: COVID-19 Type: general – SubjectFull: Reflective learning Type: general – SubjectFull: Feedback control systems Type: general – SubjectFull: Distance education Type: general – SubjectFull: Yoga techniques Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Self-evaluation Type: general Titles: – TitleFull: Artificial intelligence-supported physical education during the pandemic: a physical skill auto-assessment and feedback approach based on a reflection-promoting mechanism. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hsia, Lu-Ho – PersonEntity: Name: NameFull: Hwang, Gwo-Jen – PersonEntity: Name: NameFull: Lin, Yen-Nan – PersonEntity: Name: NameFull: Hwang, Jan-Pan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10421629 Numbering: – Type: volume Value: 73 – Type: issue Value: 3 Titles: – TitleFull: Educational Technology Research & Development Type: main |
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