文章基本信息

标题：Exploring Online Teaching Design of Curriculum Politics by Deep Learning and Visual Sensing Technology
本地全文：下载
作者：XiaoJuan Huang ; Yanhong Xie ; Yongyu Li 等
期刊名称：Computational Intelligence and Neuroscience
印刷版ISSN：1687-5265
电子版ISSN：1687-5273
出版年度：2022
卷号：2022
DOI：10.1155/2022/1283256
语种：English
出版社：Hindawi Publishing Corporation
摘要：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.