The Research on an Intelligent Management System of College Ideological and Political Courses Based on Structural Equation Modeling

In recent years, ideological and political education has played a crucial role in shaping well-rounded individuals equipped for active civic participation. As the demand for intelligent decision-support systems (IDSS) in universities grows, this study proposes an IDSS to enhance the management and delivery of Ideological and Political Education (IPE). By integrating artificial intelligence and data-driven techniques, the system supports personalized learning, decision-making, and curriculum optimization. Features include data collection, learning analytics, and individualized recommendations via machine learning. It fosters group collaboration and enhances students' understanding through an intuitive interface for both teachers and students. Structural Equation Modeling (SEM) and the ECS optimization algorithm are used to analyze the link between IPE and academic performance. Scenario results confirm the system's effectiveness in improving IPE outcomes and leadership development.

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Publication Details

Journal
International Journal of Web-Based Learning and Teaching Technologies
Published
2025-10-02
DOI
https://doi.org/10.4018/ijwltt.390456
Primary Topic
Ideological and Political Education
Type
article
Field-Weighted Citation Impact
0.00
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article

The Research on an Intelligent Management System of College Ideological and Political Courses Based on Structural Equation Modeling

Fenglin Yan, Qinjue Kang
International Journal of Web-Based Learning and Teaching Technologies
Ideological and Political Education
article

The Research on an Intelligent Management System of College Ideological and Political Courses Based on Structural Equation Modeling

Fenglin Yan, Qinjue Kang
article en

Abstract

In recent years, ideological and political education has played a crucial role in shaping well-rounded individuals equipped for active civic participation. As the demand for intelligent decision-support systems (IDSS) in universities grows, this study proposes an IDSS to enhance the management and delivery of Ideological and Political Education (IPE). By integrating artificial intelligence and data-driven techniques, the system supports personalized learning, decision-making, and curriculum optimization. Features include data collection, learning analytics, and individualized recommendations via machine learning. It fosters group collaboration and enhances students' understanding through an intuitive interface for both teachers and students. Structural Equation Modeling (SEM) and the ECS optimization algorithm are used to analyze the link between IPE and academic performance. Scenario results confirm the system's effectiveness in improving IPE outcomes and leadership development.

International Journal of Web-Based Learning and Teaching TechnologiesVol. 20(1)
Openalex Percentile: Top 70%
Ideological and Political Education
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