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Research on the Application of University Teaching Quality Based on Big Data Technology

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DOI: 10.23977/trance.2022.040201 | Downloads: 7 | Views: 199


Yun Liu 1


1 Evaluation and Quality Control Center, Nanjing University of Finance and Economic, Nanjing, Jiangsu 210023, China

Corresponding Author

Yun Liu


In the popularization stage of higher education, the development of education is not only the change of scale and quantity, but also the reality and deepening of quality connotation. This paper expounds the practical needs of high-quality development of education and university’s teaching under the background of the new era and new development pattern, investigates and analyzes the construction and use of teaching quality monitoring platforms in 34 undergraduate universities in Nanjing. Combined with the concept of educational data governance, this thesis aims to build a development path of "interconnection, co construction and sharing, integration and innovation, quality and efficiency improvement, upper and lower linkage and excellence", so as to promote the integration of teaching resources in universities, promote the investigation of management mechanism and improve the quality of building morality and cultivating people.


big data, education data governance, teaching quality evaluation, connotative development


Yun Liu, Research on the Application of University Teaching Quality Based on Big Data Technology. Transactions on Comparative Education (2022) Vol. 4: 1-9. DOI:


[1] Undavia JN, Patel S, Patel A Future trends and scopes of bigdata analytics in the field of education. Int J Eng Techno.2017, 19(3):9–14.
[2] Devedzic,V. & Devedzic, M. (2019). Technology-Enhanced Assessment at universities and in schools: An initiative. International Journal of Learning and Teaching. 11(3), 89-98. 
[3] Khan, A., Ghosh, S.K. Data mining based analysis to explore the effect of teaching on student performance. Educ Inf Technol (2018) 23, 1677–1697. 
[4] Zhang H, Fang M. Research on the integration ofheterogeneous information resources in university management informatization based ondata mining algorithms. Computational Intelligence. 2021, 37:1254–1267.
[5] Zhang Pei, Xia Haiying. Basic thinking and practice path of data governance in the field of Education. Modern educational technology, 2020, 30 (05): 19-25.
[6] Wang, H. Teaching quality monitoring and evaluation using 6G internet of things communication and data mining. International Journal of System Assurance Engineering and Management (2021),1-8
[7] Allen, C., Smith,M. ,Rabiee,M. et al. A review of scientific advancements in datasets derived from big data for monitoring the Sustainable Development Goals. Sustain Sci (2021)16, 1701–1716.
[8] Avci, C., Tekinerdogan, B.&Athanasiadis, I.N. Software architectures for big data: a systematic literature review. Big Data Anal(2020) 5,5
[9] Meng, X.- L. (2021) Enhancing (publications on) data quality: Deeper data minding and fuller data confession. Journal of the Royal Statistical Society: Series A (Statistics in Society), 184, 1161–1175.
[10] Hardy, L., Dixon, C,. Hsi, S. From Data Collectors to Data Producers: Shifting Students' Relationship to Data .Journal of The Learning Sciences.2019,9(1):104-126.

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