In order to solve the shortcomings of the traditional motion recognition methods and obtain better motion recognition effect in education, this paper pro poses a residual network based on Squeeze-and-Excitation attention mechanism. Deep residual network is widely used in various fields due to the high recognition accuracy. In this paper, the convolution layer, adjustment batch normalization layer and activation function layer in the deep residual network model are modified. Squeeze-and-Excitation (SE) attention mechanism is introduced to adjust the structure of network convolution kernel. This operation enhances the feature extraction ability of the new network model. Finally, the expansibility experiments are con17 ducted on WISDM(Wireless Sensor Data Mining), and UCI(UC Irvine) data sets. In terms of F1, the value exceeds 90%. The results show that the proposed model is more accurate than other state-of-the-art posture recognition models. The proposed method can obtain the ideal motion recognition results.

Under the artificial intelligence environment, the integration of information technology and curriculum teaching is deepening, which provides an important impetus for optimizing the classroom teaching form, integrating high-quality resources and promoting the three-dimensional upgrade of curriculum teaching. In order to realize the ideal value of ideological and political education, it is necessary to construct an intelligent ideological and political course based on the mature application of information technology, fully display the vitality of ideological and political education classroom, in order to achieve the ideal effect of ideological and political education. Through the application of artificial intelligence technology as the research background, systematically explore the integration of information technology and ideological and political courses path.