Volume 3,Issue 8
The Logical Approach of Artificial Intelligence to Empower the Development of Ideological and Political Education
Guided by Marxist theory, this study systematically explores the internal logic of AI empowerment in ideological and political education through three dimensions: technological, value-based, and practical. At the technological level, Marxist productivity theory is applied to analyze how AI optimizes educational resource allocation through tool innovation, process reengineering, and cognitive upgrading. The value-based dimension constructs a closed-loop system of "data calibration-dialectical thinking-ethical prevention," emphasizing that technology should serve human comprehensive development. Practically, Marxist theory of practice examines the theoretical pathways for transforming traditional rote teaching into intelligent interactive pedagogy. Research demonstrates that AI-enhanced ideological education must uphold Marxism's core principle of "human-centered cultivation," achieving unity between instrumental and value rationality, ultimately advancing human subjectivity and fulfilling the fundamental mission of moral education.
[1] Liu Z, 2024, A Review of AI Empowerment in Ideological and Political Education. Journal of Curriculum and Teaching, (05):99-108.
[2] Chai J, 2024, Strategies for Integrating AI Technology with Ideological and Political Education in Higher Education Institutions. Journal of Hubei Open Vocational College, (08):153-154.
[3] Ding H, Nie L Y, 2024, Exploring AI Empowerment in College Students' Ideological and Political Education. Journal of School Party Building and Ideological Education, (08):72-74.
[4] Deng H, 2024, Ethical Risks and Mitigation Strategies in AI Empowered Ideological and Political Education. Journal of Teaching in Forest Areas, (04):7-11.
[5] Zhou K, Wang X, 2024, Generative Logic, Real-world Risks, and Practical Approaches in AI Empowered Ideological and Political Education. Journal of Guangxi Science and Technology Normal University, (02):102-108.
[6] Fan C, Hu T, 2024, Paradigm Evolution and Construction Strategies for Integrating AI into Ideological and Political Education. Da Shiliwei, (02):13-17.
[7] Li H, Feng L, 2024, Positive Interaction, Risk Assessment, and Optimization Pathways in AI-empowered Ideological and Political Education. Journal of Henan University of Technology (Social Sciences Edition), (02):76-83.
[8] Xie J, Gong B, 2024, Risks and Responses in AI-empowered Military Ideological and Political Education. Journal of Political Work, (04):26-28.
[9] Pu Q, He L, 2024, The Evolution and Response of Ideological and Political Education in the Era of Artificial Intelligence. Research on Ideological Education, (03):29-35.
[10] Shen X, 2024, A Technical Logic Analysis of Integrating Artificial Intelligence Algorithms into Ideological and Political Education. China Education Informatization, (03):99-108.
[11] Zhou Y, 2024, A SWOT Analysis of Applying Artificial Intelligence to Ideological and Political Education in Higher Education Institutions. Teaching in Forest Areas, (03):23-27.
[12] Zhang H, Hu H, 2024, Value Analysis and Path Exploration of Enhancing the Effectiveness of Artificial Intelligence in Ideological and Political Education. Modern Vocational Education, (07):17-20.
[13] Feng L, Ni G, 2024, Digital Transformation of Ideological and Political Education Based on Generative Artificial Intelligence. Research on Ideological Education, (02):46-53.
[14] Yan L, Qin P, 2023, The Value, Issues, and Strategies of Empowering Ideological and Political Education with Generative Artificial Intelligence. Guangxi Social Sciences, (09):201-206.
[15] Li Y, Yan G, 2024, The Internal Logic and Path Design of Artificial Intelligence Empowering Ideological and Political Education in Higher Education Institutions. Jiangsu Higher Education, (02):84-88.