ISSN 1008-2204
CN 11-3979/C
LU Genshu, LI Zhenyan, WANG Xi. Exploration of Quality Assessment Based on Big Data Analysis in Graduate Education[J]. Journal of Beijing University of Aeronautics and Astronautics Social Sciences Edition, 2020, 33(3): 118-125. DOI: 10.13766/j.bhsk.1008-2204.2020.0059
Citation: LU Genshu, LI Zhenyan, WANG Xi. Exploration of Quality Assessment Based on Big Data Analysis in Graduate Education[J]. Journal of Beijing University of Aeronautics and Astronautics Social Sciences Edition, 2020, 33(3): 118-125. DOI: 10.13766/j.bhsk.1008-2204.2020.0059

Exploration of Quality Assessment Based on Big Data Analysis in Graduate Education

  • On the basis of summarizing the related concepts and methods of big data and big data analysis, as well as the key applications of big data analysis in the field of higher education, this paper emphatically analyzes the applications and development trend of big data analysis in the quality assessment of graduate education. Taking the project of big data analysis in quality of graduate education as an example, this paper illustrates the construction of monitoring indicator system in quality of graduate education based on big data analysis, big data collection in quality monitoring of graduate education, construction of big data analysis platform, construction and application of big data analysis model, etc. The literature review shows that the application of big data in higher education research are limited, and that the research on big data analysis in the quality of graduate education are still in its infancy. The review, however, also indicates the growing significance of big data analysis to the quality assurance of postgraduate education. Therefore, this paper puts forward several key points to strengthen the quality monitoring and assessment of graduate education driven by big data. In addition, we propose to break down the barriers between different graduate education information systems to realize the correlation between data on the premise of paying attention to data security, and actively promote the degree of integration between big data and graduate education.
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