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<p>Public physical education and dance courses, fundamental to higher education, serve dual purposes: facilitating the implementation of ideological and political coursework and achieving objectives centered around moral and educational cultivation. This study explores innovative approaches in dance education and the enhancement of civic values through a methodological framework that integrates technology and pedagogy. Initially, the research introduces a spatial-temporal graph convolutional network, innovatively designed with self-adaptive mechanisms and attention functionalities, to precisely capture dance movements. Following this keyframes within these movements are extracted using a novel method that relies on skeletal information and clustering techniques. This approach facilitates the evaluation of similarity metrics concerning joint angles between critical movement frames, thereby establishing a comparative analysis model for dance movements. The resulting scores from this model underpin the subsequent educational interventions. Subsequently, an intelligent database for dance teaching methods was developed, supporting both structured dance training and improvisational dance practices. This database aims to foster pedagogical innovation and enhance practical application in dance education. Quantitative analysis revealed significant improvements post-intervention: the average enhancement in students’ independent learning capabilities was quantified at 19.12 points. Furthermore, a statistical examination comparing pre- and post-intervention data from Class A—specifically analyzing five anatomical points: head, neck, shoulders, hips, and knees—yielded a p-value of less than 0.05, indicating significant postural improvements. Moreover, evaluations of overall civic education factors consistently exceeded a score of 3.5. Notably, the correlation coefficient between the dialectical thinking factor and the total civic score within the dance courses reached 0.88, underscoring the profound potential of dance education in bolstering civic and political education values. The integration of civic and political education content within the dance teaching process emerges as an effective pedagogical strategy, substantially elevating the level of civic and political education within university sports dance courses. This study highlights the transformative potential of integrating advanced computational techniques with traditional dance education to enhance both the pedagogical efficacy and civic engagement outcomes of higher education curricula.</p>
</abstract>

Public physical education and dance courses, fundamental to higher education, serve dual purposes: facilitating the implementation of ideological and political coursework and achieving objectives centered around moral and educational cultivation. This study explores innovative approaches in dance education and the enhancement of civic values through a methodological framework that integrates technology and pedagogy. Initially, the research introduces a spatial-temporal graph convolutional network, innovatively designed with self-adaptive mechanisms and attention functionalities, to precisely capture dance movements. Following this keyframes within these movements are extracted using a novel method that relies on skeletal information and clustering techniques. This approach facilitates the evaluation of similarity metrics concerning joint angles between critical movement frames, thereby establishing a comparative analysis model for dance movements. The resulting scores from this model underpin the subsequent educational interventions. Subsequently, an intelligent database for dance teaching methods was developed, supporting both structured dance training and improvisational dance practices. This database aims to foster pedagogical innovation and enhance practical application in dance education. Quantitative analysis revealed significant improvements post-intervention: the average enhancement in students’ independent learning capabilities was quantified at 19.12 points. Furthermore, a statistical examination comparing pre- and post-intervention data from Class A—specifically analyzing five anatomical points: head, neck, shoulders, hips, and knees—yielded a p-value of less than 0.05, indicating significant postural improvements. Moreover, evaluations of overall civic education factors consistently exceeded a score of 3.5. Notably, the correlation coefficient between the dialectical thinking factor and the total civic score within the dance courses reached 0.88, underscoring the profound potential of dance education in bolstering civic and political education values. The integration of civic and political education content within the dance teaching process emerges as an effective pedagogical strategy, substantially elevating the level of civic and political education within university sports dance courses. This study highlights the transformative potential of integrating advanced computational techniques with traditional dance education to enhance both the pedagogical efficacy and civic engagement outcomes of higher education curricula.

An In-depth Exploration of Innovative Teaching Strategies and Civic Values of Dance Education Empowered by New Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Public physical education and dance courses, fundamental to higher education, serve dual purposes: facilitating the implementation of ideological and political...

An In-depth Exploration of Innovative Teaching Strategies and Civic Values of Dance Education Empowered by New Technology

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 16. Apr. 2024

Akzeptiert: 08. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-1988

Schlüsselwörter
Attention mechanism, Spatiotemporal graph convolutional network, Skeleton information, Dance movement scoring, Civic-political value

© 2024 Zhengyi Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An In-depth Exploration of Innovative Teaching Strategies and Civic Values of Dance Education Empowered by New Technology

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 16. Apr. 2024

Akzeptiert: 08. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-1988

SchlüsselwörterAttention mechanism, Spatiotemporal graph convolutional network, Skeleton information, Dance movement scoring, Civic-political value

© 2024 Zhengyi Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Attention mechanism, Spatiotemporal graph convolutional network, Skeleton information, Dance movement scoring, Civic-political value