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IJIET 2018 Vol.8(1): 77-80 ISSN: 2010-3689
doi: 10.18178/ijiet.2018.8.1.1016

Research on Innovative Training Mode of Chinese Academic Postgraduates

G. L. Liu

Abstract—In today’s society, Chinese academic postgraduates are required to have not only technological capabilities, but also good personal credit, vocational abilities and the high professional qualities to take complete charge by fast learning. However, the traditional training mode of Chinese academic postgraduates has not been effectively combined with students’ future careers. As a result, it is hard for the postgraduates to meet actual needs of job markets. The arrival of the era of big data provides an unprecedented opportunity for innovative training of Chinese academic postgraduates. In this paper, an innovative training mode guided by vocational abilities is proposed based on big data analysis to improve the competitiveness of Chinese academic postgraduates in talent markets. Firstly, honesty education should be strengthened. Secondly, advanced teaching methods based on big data analysis should be introduced. Thirdly, the design of individualized vocational ability training programs should be supplied for each academic postgraduate based upon the data statistics and analysis of graduates’ information. Finally, behavior analysis based on big data should be used to provide early warning of mental health problems for postgraduates.

Index Terms—Big data, Chinese academic postgraduate, training mode.

G. L. Liu is with School of Science, University of Science and Technology Liaoning, Anshan, Liaoning, 114051 China (e-mail: lg_li1978@126.com).


Cite: G. L. Liu, "Research on Innovative Training Mode of Chinese Academic Postgraduates," International Journal of Information and Education Technology vol. 8, no. 1, pp. 77-80, 2018.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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