The Teaching Strategy of Socio-Political Education by Deep Learning Under Educational Psychology

Frontiers in Psychology

article

Zhen Chen¹  Lan Wen²  Xiaoqing He³  Peiyao Chen⁴  Hua Wu⁴ 

[1] School of Marxism Northeastern University Shenyang;South China Business College, Guangdong University of Foreign Studies/Faculty of Education, Guangxi Normal University;School of Marxism, Chengdu Normal University;School of History and Culture, University of Birmingham

关键词: educational psychology;    deep learning;    Social Political Education Class;    Teaching strategy;    Teaching strategies;   

DOI  :  10.3389/fpsyg.2022.910677

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

This study aims to optimize the teaching content of ideological and political courses and guide students to establish correct values. Inspired by Artificial Intelligence, the K-means clustering algorithm was applied to the neural collaborative filtering algorithm through temporal data. Besides, a deep learning algorithm was designed for the improved matrix factorization. The evaluation indicators were selected through experiments. The relevant data sets were used for simulation and testing. The test results indicated that the Root Mean Square Error of this scheme was 1.251, and the Mean Absolute Error was 0.625. These index measurement values were better than those of similar algorithms, indicating this model has better performance after optimization and can recommend suitable courses. The innovative algorithm designed to construct the classroom teaching model of social and political education can accurately recommend proper courses according to the students’ learning situation reflecting their psychological states. The research provides adaptive teaching for students, enables interaction between teachers and students, and helps students form correct values. It also has an important role in improving the teaching strategies.

【 授权许可】

CC BY