Innovative Approaches to Online Ideological and Political Education in Vocational Undergraduate Institutions in the Age of Big Data
DOI:
https://doi.org/10.70088/d5nwvz13Keywords:
big data, vocational education, political education, educational innovation, precision teachingAbstract
In the era of big data, virtually all industries are undergoing continuous and profound transformation, driven by advanced analytics and digital integration. Consequently, higher education institutions' online ideological and political education must keep pace with these contemporary technological trends. It is imperative to actively pursue innovative breakthroughs and transition from traditional, extensive teaching models to highly refined, data-driven educational approaches. This paper takes the innovation of online ideological and political education at vocational undergraduate institutions as its primary starting point. It thoroughly analyzes the current challenges inherent in modern educational practice, such as declining student engagement, outdated pedagogical methodologies, and the insufficient utilization of digital footprints. Furthermore, the study examines the unique advantages of big data in this specific context, highlighting its capacity for predictive analytics, real-time feedback, and personalized learning trajectories. To address existing deficiencies, this research proposes a comprehensive innovative pathway comprising five core dimensions: establishing a robust centralized data platform, developing individualized ideological and political student profiles, creating immersive and intelligent learning scenarios, implementing proactive risk early-warning systems, and fundamentally reforming traditional evaluation frameworks. Ultimately, the overarching aim of this study is to facilitate the sustainable development of a precise, intelligent, and highly personalized new model for online ideological and political education, thereby significantly enhancing pedagogical effectiveness and student outcomes in vocational undergraduate institutions.References
F. Zeng and L. Liu, "Improving the quality of ideological and political education in colleges and universities in big data age," in Journal of Physics: Conference Series, vol. 1852, no. 3, p. 032034, Apr. 2021, IOP Publishing.
L. Du, "Design and Realization of the Management System of Higher Vocational Students' Mental Health Based on Big Data," in 2021 International Conference on Aviation Safety and Information Technology, pp. 342-346, Dec. 2021.
J. Avis, "Socio-technical imaginary of the fourth industrial revolution and its implications for vocational education and training: A literature review," Journal of Vocational Education & Training, vol. 70, no. 3, pp. 337-363, 2018.
Z. Shi-Yong, J. Su-Ping, X. G. Yue, R. Pu, and B. Li, "Application research of an innovative online education model in big data environment," International Journal of Emerging Technologies in Learning (Online), vol. 14, no. 8, p. 125, 2019.
J. Zhu and X. Zou, "Simulation Analysis of Entrepreneurial Behavior Selection Mechanism of Higher Vocational College Students Based on Teaching Big Data," in International Conference on E-Learning, E-Education, and Online Training, Cham: Springer Nature Switzerland, pp. 553-564, Jul. 2022.
Y. Wang and L. Feng, "Vocational Education in the Era of Big Data: Course Design and Optimization Strategy Based on Educational Technology," International Journal of Interactive Mobile Technologies, vol. 18, no. 22, 2024.
G. Yang, "An Empirical Study of Quality Evaluation in Vocational Education: Based on the Culture of Big Data," Cultura: International Journal of Philosophy of Culture and Axiology, vol. 22, no. 2, pp. 170-187, 2025.
L. Wang, "Big data analysis model for vocational education employment rate prediction," Scientific Programming, vol. 2022, no. 1, p. 7576521, 2022.
T. Liu, H. Li, and H. Dong, "Vocational Education Curriculum Optimization and Intelligent Guidance System Based on Big Data," in *Proceedings of the 2024 International Conference on Big Data Mining and Information Processing*, pp. 372-377, Dec. 2024.
Y. Liu, "Construction of a dynamic evaluation model for vocational education teaching quality based on fuzzy multi-attribute decision-making," Australian Journal of Electrical and Electronics Engineering, pp. 1-17, 2025.
B. Chen, Y. Liu, and J. Zheng, "Using data mining approach for student satisfaction with teaching quality in high vocation education," Frontiers in Psychology, vol. 12, p. 746558, 2022.
E. L. Essaid and A. Azmani, "Proposal of a digital ecosystem based on big data and artificial intelligence to support educational and vocational guidance," International Journal of Modern Education and Computer Science (IJMECS), vol. 12, no. 4, pp. 1-11, 2020.
Y. Zhang, X. Sun, and J. Yu, "Transformative technologies in the evaluation of a vocational education system," Journal of Web Engineering, vol. 23, no. 2, pp. 275-298, 2024.
D. Zhaoyong, "Innovative Analysis of Ideological and Political Education for Vocational Students in the Era of Big Data," Advances in Vocational and Technical Education, vol. 4, no. 5, pp. 38-42, 2022.
H. Luan, P. Geczy, H. Lai, J. Gobert, S. J. Yang, H. Ogata, ... and C. C. Tsai, "Challenges and future directions of big data and artificial intelligence in education," Frontiers in Psychology, vol. 11, p. 580820, 2020.
X. Xu and X. Zhao, "Research on Practical Education and Innovative Application of Artificial Intelligence Large Model in Higher Vocational Education," in *Proceedings of the 9th International Conference on Electronic Information Technology and Computer Engineering*, pp. 804-808, Jun. 2025.
D. Nießen, D. Danner, M. Spengler, and C. M. Lechner, "Big five personality traits predict successful transitions from school to vocational education and training: a large-scale study," Frontiers in Psychology, vol. 11, p. 1827, 2020.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Lin Wang (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.








