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2017-2024 China Learner Portrait Research Status and Hot Spot Analysis -- Citespace visualization study based on CNKI

Jing Li

Abstract


Based on the CNKI database, the article combed the research on learner portrait between June 2017 and June 2024, and analyzed
the number of articles, the cooperation network of scholars, keywords, and other related contents to summarize the current situation and hot
spots of the research on learner portrait in China. The results show that the hot topics of research mainly focus on Student Portrait, Learner
Portrait, User Portrait, Big Data, Learning Analysisand so on, show much research innovation and integration. The related research
involves a variety of fields, such as educational technology, pedagogy, computer information technology, and so on. From June 2017 to June
2024, the research hot spots gradually expanded from the application of data technology to the field of education, reflecting the trend of the
integration of education and technology. The hot spots gradually shifted from applying technologies such as user portrait technology and big
data to the specific application and development of the education field such as learning portrait, comprehensive quality education, smart campus, digital portrait, precise ideology, and teaching intervention. The research results provide important theoretical and practical guidance for
education information technology and smart education.

Keywords


Learner portrait; Student portrait; Big data; Smart campus

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References


[1] Sun, F. Q., Dong, W. Chun. (2020). Research on online learning user profiling based on learning analysis. Modern Educational Technology, 30(4): pp.5-11.

[2] Li, C. H., Wang, Q. L.. (2018). A Review of Research on Learner Portrait Construction and Application. China Electrochemical Education, (8), 18-23.

[3] Aleksieva-Petrova, A., M. Petrov, M., (2023). Data Merging for Learning Analysis in Learning Environments. Learning in the Age of

Digital and Green Transition, no.1, pp. 752-759

[4] Dmello, V. J., Jagannathrao, V., Rajendran, A., Bidi, S. B., Ghosh, T., Kaur, J., & Haldorai, K. (2023). "Antecedents promoting e-learner's

engagement behavior: mediating effect of e-learner's intention to use behavior. "Cogent Education, 10(2).

[5] Ye, Y.P., Lan, D.C., and Zhou, X.. (2023)." Visual analysis of hot spots and trends in domestic library user profile research." Intelligence

Science 41.10. pp. 164-176.

[6] Chen, H. J., et al. (2017)." Exploring Learner Profiling and Personalized Instruction under Open Learning." Open Education Research

23.03:105-112.

[7] Zhu, Z. X., et al. (2018) "Analysis of student behavioral portrait based on data analysis." China Education Information.23:21-23.

[8] Xu Q., et al. (2022)." A study on performance prediction based on learner profiles in online education environment." Exam Research.

05:89-99.

[9] Ge Kun, Xu Haifeng, and Liu Xiaoyuan. (2024)." Status, hot spots and frontiers of artificial intelligence teaching research in colleges

and universities." Higher Education Forum.06:13-18+82.

[10] Guo Yuan, and Xie Tan." Visual analysis of research hot spots for accurate portrait construction of college groups in the era of big data."

Journal of Changzhou Institute of Information Vocational Technology 23.03(2024):22-28+40.

[11] Dong Ye (2023)." Research on precise ideological politics in colleges and universities based on students' portraits." Jiangsu Higher

Education.09:110-113.




DOI: http://dx.doi.org/10.18686/wef.v2i4.4597

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