Tai Chi martial arts education is one of the components of school education. Its educational value is not only to require students to master basic Tai movement technical skills and improve their physical fitness but also to bring students’ ideological progress and cultivate students to respect teachers and lectures. Excellent moral qualities such as politeness, keeping promises, observing the rules, and acting bravely, as well as the cultivation of the spirit of unity and cooperation, and the quality of will also have a certain meaning. However, the scientific Tai Chi ideological and political courses and the construction of Wude education interactive classrooms lack relevant research. Therefore, this article builds a Tai Chi ideological and political interactive classroom system based on big data technology and graph neural network. First, the spatio-temporal graph convolutional neural network is used to reason about the relationship between Tai Chi action categories and strengthen the low-dimensional features of semantic categories and their co-occurrence expressions used for semantic enhancement of current image features. In addition, in order to ensure the efficiency of the Tai Chi scene analysis network, an efficient dual feature extraction basic module is proposed to construct the backbone network, reducing the number of parameters of the entire network and the computational complexity. Experiments show that this method can obtain approximate results, while reducing the amount of floating-point operations by 42.5% and the amount of parameters by 50.2% compared with the work of the same period, and achieves a better balance of efficiency and performance. Secondly, based on the big data of historical Tai Chi classrooms, this article constructs an interactive classroom system that can effectively improve the quality of Tai Chi ideological and political courses.

中文翻译：

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基于大数据和图神经网络的大学太极拳思想政治课分析

太极武术教育是学校教育的组成部分之一。它的教育价值不仅是要求学生掌握基本的太极拳运动技术技能，提高他们的身体素质，而且还应带给学生思想上的进步，并培养学生尊重老师和讲课的能力。礼貌，信守诺言，守规矩，勇敢行事等良好的道德品质，对团结合作精神的养成和意志的品质也有一定的意义。但是，科学的太极拳思想政治课程和武德教育互动教室的建设尚缺乏相关的研究。因此，本文构建了基于大数据技术和图神经网络的太极思想政治互动课堂系统。第一的，时空图卷积神经网络用于推理太极拳动作类别之间的关系，并增强语义类别的低维特征及其用于当前图像特征语义增强的共现表达。另外，为了保证太极拳场景分析网络的效率，提出了一种高效的双特征提取基本模块来构建骨干网络，从而减少了整个网络的参数数量和计算复杂度。实验表明，与同期工作相比，该方法在减少浮点运算量42.5％，减少参数量50.2％的同时，可获得近似结果，达到了效率与性能的更好平衡。第二，