Tripartite Synergy in Postgraduate Education: Integrating Ideological-Political Cultivation, Industry-Academia Symbiosis, and Frontier-Driven Pedagogy in Regional Universities

Baofeng Ji; Xiaoyang Jiang; Ziyang Wen; Zhiyuan Gu; Yunran Chen; Shimeng Gao; Jingjing Guo

doi:10.6918/IJOSSER.202505_8(5).0003

Authors

Baofeng Ji
Xiaoyang Jiang
Ziyang Wen
Zhiyuan Gu
Yunran Chen
Shimeng Gao
Jingjing Guo

DOI:

https://doi.org/10.6918/IJOSSER.202505_8(5).0003

Keywords:

Graduate education; 5G industrial internet; Industry-teaching integration; Civic education; Cutting-edge technology.

Abstract

This paper, based on the Exemplary Teaching Case Project (ETCP) for Professional Degree Graduate Students in Henan Province, addresses three systemic deficiencies in regional graduate education: (1) the dichotomy between theory and practice in the teaching of technology; (2) the ineffectiveness of industry-teaching integration; and (3) the lagging uptake of cutting-edge technologies. This paper proposes a pedagogical framework that integrates 5G-enabled industrial internet technologies (including wireless communication principles, modern digital communication systems, and cutting-edge communication technologies) with URLLC (ultra-reliable low-latency communication) infrastructure deployed at Longmen Labs. We have constructed an interdisciplinary integration mechanism for postgraduate education, integrating ideological and political inculcation, industry practice and cutting-edge technology absorption. Through systematic case analysis and empirical investigation, nine evidence-based teaching reform propositions were put forward. A prototype deployment in CITIC Heavy Industry’s smart manufacturing sector demonstrated its operational effectiveness, thereby establishing a replicable framework for regional higher education transformation.

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References

[1] Eryong X, Li J. What is the ultimate education task in China? Exploring “strengthen moral education for cultivating people” (“Li De Shu Ren”) [J]. Educational Philosophy and Theory, 2021, 53(2): 128-139.

[2] Zhou J, Li P, Zhou Y, et al. Toward new-generation intelligent manufacturing[J]. Engineering, 2018, 4(1): 11-20.

[3] Guo H, Sun J, Zhang Y S. Research on the teaching method of the integration of curriculum ideology and professional courses[C]//6th International Conference on Humanities and Social Science Research (ICHSSR 2020). Atlantis Press, 2020: 205-208.

[4] Zhinuo L, Keliang J, “Research on Ideological and Political Teaching Mode in Professional Courses in Colleges”, Atlantis Press, vol. 22, no. 25, pp. 2352-5398, 2021.

[5] Seol Y, Hyeon D, Min J, et al. Timely survey of time-sensitive networking: Past and future directions[J]. Ieee Access, 2021, 9: 142506-142527.

[6] Stüber T, Osswald L, Lindner S, et al. A survey of scheduling algorithms for the time-aware shaper in time-sensitive networking (TSN)[J]. Ieee Access, 2023, 11: 61192-61233.

[7] Ahmad A. Industrial engineering technology curriculum remapping[C]//2015 ASEE Annual Conference & Exposition. 2015: 26.956. 1-26.956. 10.

[8] Cheminod M, Durante L, Valenzano A. Review of security issues in industrial networks[J]. IEEE transactions on industrial informatics, 2012, 9(1): 277-293.

[9] Yueping C, Xiaowen Z ,Shaoliu H, et al. “Dynamic QoS Mapping and Adaptive Semi-Persistent Scheduling in 5G-TSN Integrated Networks”, China Communications, vol. 20, no. 4, pp. 340-355, 2023.

[10] Meira J, Matos G, Perdigão A, et al. Industrial Internet of things over 5G: A practical implementation [J]. Sensors, 2023, 23(11): 5199.

[11] M. B. Caamaño, L. M. Contreras, J. V. Martínez, et al, “Reliability in deterministic networks: Comparison of FRER (TSN) and PREOF (DetNet)”, 2024 24th International Conference on Transparent Optical Networks (ICTON), Bari, Italy, pp. 1-4, 2024.

[12] Sasiain J, Franco D, Atutxa A, et al. Towards the integration and convergence between 5G and TSN technologies and architectures for industrial communications: A survey[J]. IEEE Communications Surveys & Tutorials, 2024.

[13] Wang Z. Digital twin technology[M]//Industry 4.0-impact on intelligent logistics and manufacturing. IntechOpen, 2020.

[14] Liu Y, Peng M, Shou G, et al. Toward edge intelligence: Multiaccess edge computing for 5G and Internet of Things[J]. IEEE Internet of Things Journal, 2020, 7(8): 6722-6747.

[15] Bank C, Securities C, Steel C P S, et al. Our company[EB/OL].(2020)

[16] Xuelong L, Kang L, Yongsheng D, et al, “Patch Alignment Manifold Matting”, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 7, pp. 3214-3226, 2018.