Research on the Education and Teaching of Physical Education Dance Courses in Colleges and Universities Based on Deep Learning

Teaching reform is usually a unified adjustment based on the current teaching objectives, lacking pertinence. In order to improve the teaching quality and students’ learning quality of sports dance course in colleges and universities, according to the teaching quality evaluation data, this paper proposes the teaching method of sports dance course in colleges and universities based on in-depth learning. According to the sports dance action image after the visual error correction, the OpenPose human posture estimation algorithm is used to implement the dancer’s motion posture estimation, obtain the sequence data of the dancer’s skeleton joint points, and use the depth convolution neural network optimized by particle swarm optimization algorithm to build the sports dance action recognition model, with the obtained sequence data of the dancer’s skeleton joint points as the effective input. The result of sports dance movement recognition is obtained through training, which is used as the basis for students to correct their dance movements and improve their professional skills. According to the teaching process organized by teachers and the goal of cultivating students’ professional skills, a sports dance teaching evaluation index system is constructed, and the deep convolution neural network optimized by particle swarm optimization algorithm is used to build a sports dance teaching evaluation model. With the quantified data of the secondary indicators in the teaching evaluation index system as the model input, the sports dance teaching evaluation results are obtained through training. The findings will serve as a dependable foundation for educators to enhance the quality of instruction and assist students in enhancing their proficiency in sports dance. The experimental outcomes demonstrate that this approach is adept at identifying sports dance movements effectively and precisely evaluating sports dance classes, thereby establishing a solid footing for substantially boosting the instructional impact of sports dance courses in higher education institutions.

Authors

Publication Details

Journal
International Journal of High Speed Electronics and Systems
Published
2024-12-27
DOI
https://doi.org/10.1142/s012915642540172x
Citations
1
Primary Topic
AI and Multimedia in Education
Type
article
Field-Weighted Citation Impact
0.35
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article

Research on the Education and Teaching of Physical Education Dance Courses in Colleges and Universities Based on Deep Learning

Yangliu, Gaomingyang, Xuwenfeng
1 citations
International Journal of High Speed Electronics and Systems
AI and Multimedia in Education
0.35
article

Research on the Education and Teaching of Physical Education Dance Courses in Colleges and Universities Based on Deep Learning

Yangliu, Gaomingyang, Xuwenfeng
article en
1 citations

Abstract

Teaching reform is usually a unified adjustment based on the current teaching objectives, lacking pertinence. In order to improve the teaching quality and students’ learning quality of sports dance course in colleges and universities, according to the teaching quality evaluation data, this paper proposes the teaching method of sports dance course in colleges and universities based on in-depth learning. According to the sports dance action image after the visual error correction, the OpenPose human posture estimation algorithm is used to implement the dancer’s motion posture estimation, obtain the sequence data of the dancer’s skeleton joint points, and use the depth convolution neural network optimized by particle swarm optimization algorithm to build the sports dance action recognition model, with the obtained sequence data of the dancer’s skeleton joint points as the effective input. The result of sports dance movement recognition is obtained through training, which is used as the basis for students to correct their dance movements and improve their professional skills. According to the teaching process organized by teachers and the goal of cultivating students’ professional skills, a sports dance teaching evaluation index system is constructed, and the deep convolution neural network optimized by particle swarm optimization algorithm is used to build a sports dance teaching evaluation model. With the quantified data of the secondary indicators in the teaching evaluation index system as the model input, the sports dance teaching evaluation results are obtained through training. The findings will serve as a dependable foundation for educators to enhance the quality of instruction and assist students in enhancing their proficiency in sports dance. The experimental outcomes demonstrate that this approach is adept at identifying sports dance movements effectively and precisely evaluating sports dance classes, thereby establishing a solid footing for substantially boosting the instructional impact of sports dance courses in higher education institutions.

International Journal of High Speed Electronics and Systems
Quality Education
Openalex Percentile: Top 30%
AI and Multimedia in Education
0.35
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Research on the Education and Teaching of Physical Education Dance Courses in Colleges and Universities Based on Deep Learning — Yangliu, Gaomingyang, et al. · International Journal of High Speed Electronics and Systems (2024) | TGRS Research Map | TGRS