大数据背景下高校学生对精准资助工作满意度的研究——基于重庆市高校学生的调查

Research on College Students’ Satisfaction with Precision Funding Work under the Background of Big Data——Based on the Investigation of College Students in Chongqing

“精准扶贫”在高校的体现就是对学生的精准资助,利用大数据可以提高对学生资助的精准度。基于已有的研究及对重庆市八所大专院校学生的问卷调查,构建一个关于影响高校学生对目前高校精准资助工作满意度的系统模型。实证研究结果表明:在对高校学生进行资助时,充分考虑学生的个人消费特征数据、家庭经济状况数据、认定的民主程度以及提高学校的资助政策宣传及资助效果,能够显著正向提高学生对高校精准资助工作的满意度。若高校资助偏袒于学生干部,则会降低学生对资助工作的满意度;资助是否考虑学生的其他在校表现与学生的资助满意度无显著相关关系;最后根据实证结论提出利用大数据创新高校精准资助工作,提高学生满意度的政策建议。

The embodiment of “precise poverty alleviation” in colleges and universities is the accurate funding for students. Using big data can improve the precision of the student financial assistance. Based on the research and the questionnaire survey of the students in eight colleges in Chongqing, a systematic model affecting the satisfaction of college students with the work of precision subsidy in colleges and universities at present is established. The results of empirical research show that when funding college students, considering the students’ personal consumption characteristics data, family economic status data, the degree of democracy determined and the promotion of school funding policies and funding effects can significantly improve the students’ satisfaction with the precision funding of colleges and universities. If college funding is biased towards the student cadres, it will reduce students’ satisfaction. There is no significant correlation between whether considering students’ other school performances and student funding satisfaction. Finally, according to the empirical conclusion, this paper puts forward some policy suggestions on using big data to innovate the precision subsidy work in colleges and universities to improve the students’ satisfaction.