Exploring Online Teaching Design of Curriculum Politics by Deep Learning and Visual Sensing Technology

The study aims to explore the online teaching design of ideological and political education (IPE). Based on the relevant theories of deep learning (DL) and visual sensing, the students of a Chinese University are taken as the research samples and investigated by a questionnaire survey. Then, DL and visual sensing are introduced into the online teaching design of IPE, and the research conclusions are obtained. The results show that college students are interested in IPE, but there are still some problems in the actual teaching process. For example, 60% of the students do not know the learning objectives of IPE, and 19.7% are not familiar with the learning contents; based on the image semantic analysis of the curriculum of IPE, DL mainly focuses on model construction and data processing, and visual sensing is used to classify image pixels; the students' concentration time is changed from 29 minutes to 30.4 minutes, and their efficiency of homework submission is also improved based on DL and visual sensing. The study has a great reference for ideological and political teaching in the future.