Research on Development Strategies for Empowering Ideological and Political Education in Higher Education Institutions Through Algorithmic Recommendation Technology

Xubin Wang

doi:10.70393/616a736d.343030

OPEN ACCESS |Research Article ||20 March 2026

Research on Development Strategies for Empowering Ideological and Political Education in Higher Education Institutions Through Algorithmic Recommendation Technology

Xubin Wang

Xinjiang Normal University

1485225573@qq.com

Xinjiang Normal University, CN, 1485225573@qq.com.

* Corresponding Author¹: Xubin Wang, E-Mail: 1485225573@qq.com

Publication

Accepted 2026 March 4 ; Published 2026 March 20

Academic Journal of Sociology and Management, 2026, 4(2), 3005-5040.

Abstract

Abstract: As the primary arena for conducting and implementing ideological and political education, universities must adapt to the tide of development in the digital age.Algorithm recommendation technology, as a vital component of emerging digital-age technologies, holds significant importance for advancing the high-quality development of ideological and political education in higher education institutions. It is essential to actively explore the theoretical basis and practical foundation for leveraging algorithm recommendation technology to empower ideological and political education, while clarifying its critical value in this context. Concurrently, development strategies should be strengthened across three dimensions—technology, stakeholders, and institutional frameworks—to enhance the educational effectiveness of ideological and political education in higher education institutions.

Keywords

Algorithmic Recommendation , Ideological and Political Education , University Students , Development Strategy .

Metadata

DOI:

10.70393/616a736d.343030

ARK:

ark:/40704/AJSM.v4n2a01

Pages: 1-6

References: 7

Disciplines: Education

Subjects: Higher Education Studies

Cite This Article

APA Style

Wang, X. (2026). Research on development strategies for empowering ideological and political education in higher education institutions through algorithmic recommendation technology. Academic Journal of Sociology and Management, 4(2), 1-6. https://doi.org/10.70393/616a736d.343030

Acknowledgments

Not Applicable.

FUNDING

Not Applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not Applicable.

DATA AVAILABILITY STATEMENT

Not Applicable.

INFORMED CONSENT STATEMENT

Not Applicable.

CONFLICT OF INTEREST

Not Applicable.

AUTHOR CONTRIBUTIONS

Not application.

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Cohn, J. (2019). The burden of choice: Recommendations, subversion, and algorithmic culture. Rutgers University Press.

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Milano, S., Taddeo, M., & Floridi, L. (2020). Recommender systems and their ethical challenges. AI & Society, 35(4), 1–11.

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