Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

March 10, 2023


Pages


DOI

Article

The application of video text generation technology in assessing the effectiveness of teaching ethnic traditional sports

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Authors

Zhi Tang Affiliation:
College of Sports, Hunan University of Science and Engineering, Yongzhou, Hunan, 425199, China
and Dongdong Wang Affiliation:
College of Sports Education, Guangzhou Sport University, Guangzhou, Guangdong, 510630, China


Abstract

Ethnic traditional sports are forms of physical activity unique to one or more ethnic groups. Effective evaluation of the teaching effectiveness of ethnic traditional sports helps to promote the development of ethnic sports and the transmission of ethnic traditional sports. Currently, the evaluation of ethnic traditional sports is mainly a scoring system, which evaluates students’ performance in ethnic traditional sports through teachers’ scoring, and this evaluation method is difficult to assess the teaching effectiveness of ethnic traditional sports accurately. In this paper, based on the video text generation technology, the 3D residual attention network model is constructed by introducing the attention mechanism into the 3D residual module in the video feature extraction through the encoding-decoding video text description framework and improving the traditional deep residual network for evaluating the teaching effect of ethnic sports. After experimental validation, it is shown that the 3D residual attention network model can more accurately describe the evaluation of ethnic traditional sports teaching effectiveness using natural language.


Keywords

Ethnic traditional sports, Teaching effectiveness evaluation, Video text generation technique, 3D residual attention network, 68Q32


Citation

Tang, Z. & Wang, D. (2023). The application of video text generation technology in assessing the effectiveness of teaching ethnic traditional sports. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00023

Published by: Engineering Journals

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