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.

Details

Title
Construction of a teaching mechanism for ideological and political theory courses in universities based on deep learning theory
Author
Wang, Haiyan 1 ; Wang, Wenping 1   VIAFID ORCID Logo  ; Fan, Qian 2 ; Simi Rong 1 ; Liu, Yiting 1 

 School of Marxism, Liaoning University, Shenyang, China 
 School of Economy, Liaoning University, Shenyang, China 
Publication year
2024
Publication date
Jan 2024
Publisher
Taylor & Francis Ltd.
e-ISSN
2331186X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3158499037
Copyright
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.