高校精准识别资助对象的动态优先管理机制

Dynamic Priority Management Mechanism for Identifying Accurate Funding Objects in Universities

高校资助对象的精准识别应建立在大数据基础上,在制度限制的框架下,将严谨、合理的数据与柔性的人文关怀相结合,以育人成才为最终目的。影响高校资助对象精准识别效果的客观因素是技术异化带来的依赖性,主观因素包括缺乏人文关怀,数据更新不及时,主体参与性不足与客体异化等。动态优先的精准识别模型由识别优先的资助对象基础信息收集子系统、帮扶优先的师生交流互动子系统、关注优先的资助政策落实子系统构成,最终目的是确保真正家庭经济困难的学生能够进入资助对象体系,并得到有针对性的、及时的资助与帮扶。模型建立之后,以大数据整合的方式覆盖全体学生,将困难认定条件的数据筛查和人文关怀相结合,这将成为资助工作开展的重要方式。

The precise identification of university-funded objects should be based on big data.Under the institutional constraints,that educating people to become talents will be the ultimate goal in the combination of rigorous and reasonable data with soft humanistic care.The objective factors affecting the precise identification effect of university-funded objects are the dependence caused by technological alienation.Also,subjective factors include the lack of humanistic care,late updated data,insufficient subject participation and object alienation and so on.The dynamicpriority precision identification model consists of a basic funded objects information collection subsystem that prioritizes identification,a teacher-student communication and interaction subsystem that prioritizes assistance,and a funding policy implementation subsystem that prioritizes attention.The ultimate goal of dynamic-priority precision identification model is to ensure that the students with real family financial difficulties can enter the funding target system and receive targeted and timely funding and assistance.After the model is established,all students will be covered by the integration of big data,and the unit of data screening and humanistic care for difficult-to-identify conditions will be integrated.This will become an important way to develop funded work.