Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Information and Knowledge Management
  4. Vol 4, Issue 4, 2023

Analysis of Hot Research Topics on Chinese Data Literacy Based on Bibliometrics

Download as PDF

DOI: 10.23977/infkm.2023.040411 | Downloads: 11 | Views: 346

Author(s)

Wei Jiansong 1, Liu Jiting 2

Affiliation(s)

1 Nanchang Normal University, Nanchang, China
2 Yichun Vocational and Technical College, Yichun, China

Corresponding Author

Wei Jiansong

ABSTRACT

Data literacy has become an essential basic literacy for individuals living in the digital age. Reviewing published literature on data literacy topics helps clarify the research framework related to data literacy and further optimize subsequent related studies. Through collecting, organizing, and cleansing academic papers published in SCI, EI, CSSCI, CSCD, and Peking University core journals included in CNKI, a bibliometric analysis was conducted to systematically review the research framework of data literacy. Currently, Chinese scholars have made preliminary explorations in the connotation and value research of data literacy, the evaluation of data literacy capabilities, and the path of data literacy cultivation. By utilizing CiteSpace analysis, it was found that "data-driven" is the latest emergent term in research related to data literacy, which may represent the cutting-edge research in the field of data literacy in the current academic community.

KEYWORDS

Data literacy; Knowledge graph; Bibliometrics

CITE THIS PAPER

Wei Jiansong, Liu Jiting, Analysis of Hot Research Topics on Chinese Data Literacy Based on Bibliometrics. Information and Knowledge Management (2023) Vol. 4: 69-78. DOI: http://dx.doi.org/10.23977/infkm.2023.040411.

REFERENCES

[1] Ding, X., Wu, Q., Zhang, P., et al. (2022). Analysis of the Current Research Status of Management Science and Engineering in China Based on International authoritative Journals. Management Journal, 19(2), 159-168.
[2] Yu, L., Wang, Z. (2018). Applicability and Improvement of Z-index Evaluation of Academic Journals. Journal of Information Science, 37(11), 1132-1139.
[3] He, J., Ge, J., Zhang, F., et al. (2021). World Contributions of Chinese Scholars in Management Research: International Cooperation, Frontier Hotspots, and Contribution Paths—A Quantitative Analysis Based on World Thousand Management English Journals Papers (2013–2019). Management World, 37(9), 36-67.
[4] Hou, J., Liu, B. (2015). The Matthew Effect in the Output of Journal Evaluation Research. China Science and Technology Journal Research, 26(9), 992-996.
[5] Meng, X., Chang, E., Ye, L. (2016). Research on Data Literacy: Origin, Current Situation, and Prospects. Journal of Library Science in China, 42(2), 109-126.
[6] Zhang, J., Li, B. (2015). Connotation, Value, and Development Path of Teacher Data Literacy in the Background of Big Data. Research on Educational Technology, 36(7), 14-19, 34.
[7] Zhao, H. (2017). Professional Development of Primary and Secondary School Teachers Based on Data Literacy: Connotation and Path. Continuing Education Research, (10), 77-80.
[8] Jia, P., Song, N. (2020). Data Literacy of Middle School Students in the Era of Big Data: Connotation, Value, and Constituent Dimensions. Research on Educational Technology, 41(12), 28-34, 58.
[9] Zhang, M., Zhou, Y. (2016). Targeting and System Construction of University Students' Data Literacy Education in the Era of Big Data. Library, (10), 84-88.
[10] Deng, L., Yang, W. (2017). Research Progress on Individual Data Literacy Evaluation System and Related Indicators. Library and Information Service, 61(3), 140-147.
[11] Long, Q. (2015). Construction of the Indicator System for Data Literacy and Investigation and Analysis of Data Literacy Abilities of College Teachers and Students. Library, (12), 51-56, 62.
[12] Li, Q., Zhao, H. (2018). Research on the Evaluation Indicator System of Teacher Data Literacy. Research on Educational Technology, 39(10), 104-110.
[13] Ma, T., Sun, L. (2019). Evaluation of Data Literacy of College Students in the Perspective of Information Ecology. Information Science, 37(8), 120-126.
[14] Hui, G., Zeng, L. (2021). Data Literacy in the Intelligent Era: Model Construction, Indicator System, and Training Path—A Comparative Analysis Based on Domestic and Foreign Models. Journal of Distance Education, 39(4), 52-61.
[15] Chen, J., Sun, X., Yang, B. (2022). Evaluation Framework and Implementation Path of Data Analysis Literacy. Journal of Mathematics Education, 31(2), 8-12, 57.
[16] Hao, Y., Shen, T., Gao, S. (2015). Reflections and Suggestions on the Practice of Data Literacy Education in Universities—Based on the Analysis of Harvard University Cases and Interviews with Chinese Library and Information Professionals. Library and Information Work, 59(12), 44-51.
[17] Zhang, B., Liu, S., Liu, Z., et al. (2017). Research on the Training Strategy of Data Literacy for Normal Students Based on Big Data. Research on Educational Technology, 38(12), 86-91, 120.
[18] Hu, Y., Zhang, Q., Sun, K., et al. (2022). Research on the Cultivation Model and Application of Data Literacy for Primary and Secondary School Teachers. China Distance Education, (3), 51-60.
[19] Zhang, J. (2016). Research on the Cultivation of Research Personnel's Data Literacy in the Context of the Fourth Paradigm of Science. Journal of Library and Information, (2), 133-136.
[20] Wang, S. (2020). Data-Driven Library and Information Science: An Overview of Hot Topics in Library and Information Science in 2019. Information Work of Intelligence, 41(1), 39-44.
[21] He, Y., Zhao, Q., Xiao, P. (2020). Library Strategic Planning and Implementation Strategies in the Data-Driven Era. Library Tribune, 40(11), 98-104.
[22] Zhao, Y., Zhou, B. (2021). Discipline Librarian 3.0 and the Construction of Its Service System. Library Research, (14), 79-86.
[23] Gu, J., Yang, X., Zheng, X., et al. (2020). The Logical Framework and Practical Exploration of Data-Driven Modernization of School Governance. Modern Distance Education Research, 32(5), 25-34.
[24] Chen, X. (2020). The Development Path of Data-Driven Teaching Reform in Universities. Education Theory and Practice, 40(33), 52-55.
[25] Yang, X., Guo, L., Wang, D., et al. (2020). Modernization of Data-Driven Education Governance: Practice Framework, Real Challenges, and Implementation Paths. Modern Distance Education Research, 32(2), 73-84.
[26] Zhong, Y., Wu, Z., Chen, X. (2021). Data-Driven Precision Training: Theoretical Connotations, Implementation Framework, and Promotion Paths. Journal of Sports Science, 41(12), 48-61.
[27] Yuan, L., Zhang, J. (2021). Reflections on Empowering the Leadership of Teachers in the New Era with Data-Driven Approaches. Contemporary Education Forum, (1), 82-88.
[28] Wei, Y., Zhang, L. (2022). From "Experience-Based" to "Data-Driven": A New Teaching Paradigm in the Era of Big Data. Contemporary Educational Science, (02), 50-56.

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

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.