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高等学校贫困生资助工作利用大数据思考

Application of Big Data to Financial Assistance for Poor Students in Colleges and Universities

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【作者】 李平则杨志峰

【Author】 LI Ping-ze;YANG Zhi-feng;College of Urban and Rural Construction, Shanxi Agricultural University;College of Physical Education, Shanxi Agricultural University;

【机构】 山西农业大学城乡建设学院山西农业大学体育学院

【摘要】 高等学校贫困生资助工作是国家扶贫工作的重要组成部分,关乎教育公平、大学生成长、校园稳定和社会进步。随着大学生人数的不断增加,传统的高等学校贫困生资助工作难以达到"精准资助"的现实要求,贫困生识别精准度低、资助育人效果不明显和缺乏动态监管等问题逐渐凸显。对此,要树立以生为本理念,以大数据为依托,加强数据保密,通过打通贫困生资助工作信息平台,协同开展大数据精准资助与精准育人,加强贫困生资助线上线下双向监管,提升高等学校贫困生资助工作精准度,实现前瞻性资助和动态化管理。

【Abstract】 The financial assistance for poor college students is a matter of educational equality, student growth,campus stability and social progress as an important part of poverty reduction in the country. The increasing number of university students brings problems to the financial assistance for poor college students, such as the failure in targeted finical assistance, the difficulty in accurate identification of poor students, the less obvious finance-assisted education and the lack of dynamic supervision. For this reason, human-centered thinking should be developed, and big data applied to strengthening data confidentiality and opening up the information platform of financial assistance for poor college students, targeted financial assistance and targeted education, and strengthening both online and offline supervision of financial assistance for poor college students, so as to improve the accuracy of financial assistance for poor college students and achieve forward-looking financial assistance and dynamic administration.

【基金】 山西农业大学党建研究项目(2018DJYJ008)
  • 【文献出处】 沈阳农业大学学报(社会科学版) ,Journal of Shenyang Agricultural University(Social Sciences Edition) , 编辑部邮箱 ,2019年01期
  • 【分类号】G647
  • 【被引频次】9
  • 【下载频次】100
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