ISSN 1008-2204
CN 11-3979/C
陆根书, 李珍艳, 王玺. 大数据分析在研究生教育质量评价中的应用探析[J]. 北京航空航天大学学报社会科学版, 2020, 33(3): 118-125. DOI: 10.13766/j.bhsk.1008-2204.2020.0059
引用本文: 陆根书, 李珍艳, 王玺. 大数据分析在研究生教育质量评价中的应用探析[J]. 北京航空航天大学学报社会科学版, 2020, 33(3): 118-125. DOI: 10.13766/j.bhsk.1008-2204.2020.0059
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

大数据分析在研究生教育质量评价中的应用探析

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

  • 摘要: 在归纳总结大数据与大数据分析的相关概念和方法、高等教育大数据分析关键应用的基础上,重点分析了大数据分析在研究生教育质量评价中的应用与发展趋势。以"研究生教育质量大数据分析专项研究"项目为例,对基于大数据分析的研究生教育质量监测指标体系构建、大数据采集、大数据分析平台建设、大数据分析模型建构及应用等进行简要概述。研究发现:大数据与高等教育发展的融合程度仍较低;研究生教育大数据分析技术发展还不成熟,有待不断完善和发展;基于大数据分析的监测评估将是研究生教育质量评估的发展趋势。为此,提出开展大数据驱动的研究生教育质量监测与评价需要加强的三个关键环节,指出要在注意数据安全性的前提下,打破研究生教育不同业务系统数据之间的壁垒,实现数据间的关联,积极推进大数据与研究生教育之间的融合程度。

     

    Abstract: 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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