【摘要】 对高校家庭经济困难学生进行资助是实现社会公平的一种最直接和有效的路径,而对他们进行精准资助的前提是对家庭经济困难学生的精准识别和认定。当前我国高校家庭经济困难学生认定中存在贫困证明材料失真、家庭经济困难学生认定缺乏科学标准、家庭经济困难学生认定缺乏动态化管理三个主要问题。大数据运用于高校家庭经济困难学生认定中,可以打破信息不对称,有利于隐性家庭经济困难学生的发掘,有利于精准资助工作开展。为了更好地发挥大数据在家庭经济困难学生认定中的作用,应该加强大数据人才队伍的建设,加大对家庭经济困难学生数据的采集,采用定量和定性相结合的方法进行认定。更多还原

【Abstract】 Subsidizing students with financial difficulties in families in colleges and universities is one of the most direct and effective ways to achieve social fairness. The premise of providing them with precise grants is to accurately recognize and identify students with financial difficulties. At present, there are three major problems in the identification of students with financial difficulties in colleges and universities in China: the distortion of poverty proof materials, the lack of scientific standards for those students with financial difficulties, and the lack of dynamic management of identification of students with financial difficulties. The use of big data in students identified with financial difficulties in colleges and universities can break the asymmetry of information, benefit the excavation of students with recessive financial difficulties, and benefit the development of accurate subsidy work. In order to give full play to the role of big data in the identification of students with financial difficulties, we should strengthen the building of big data talent team, increase the collection of data of students with financial difficulties, and adopt the combination of quantitative and qualitative methods.更多还原