Construction of a teaching mechanism for ideological and political theory courses in universities based on deep learning theory

Abstract

This study focuses on the problem of ‘teachers’ teaching’ and ‘students’ learning’ in college education courses. It aims to introduce the Deep Learning theory into the teaching of ideological and political theory courses in universities; deepen the theoretical framework of education courses and the associated learning, maintenance, promotion, and support mechanisms; and realise the modernisation of teaching ideas and strategies. A quantitative and qualitative questionnaire survey was used to analyse respondents’ learning experience and effect. Most participants had a significant learning experience and effect under the DL mechanism, a large sense of gain, and a strong cognition and acceptance of IPTCs. We also found positive correlations between whether participants chose political subjects and their learning motivation and interest, between classroom attention and overall sense of gain, and between learning interest and overall sense of gain. The results can inform teaching innovations, optimise teaching strategies, and improve the teaching effect of IPTCs in the digital education era.

Keywords

• Deep learning
• ideological and political theory course
• teaching concept
• teaching mechanism
• Stephen Darwin, Universidad Alberto Hurtado, Chile
• Education Policy & Politics