基于食堂消费大数据分析的精准资助对策研究——以湖南科技大学为例  

A Strategy Study of Targeted Subsidization Based on Big Data of Canteen Consumption:A Case Study of Hunan University of Science and Technology

作　　者：赵前程[1] 王艳 梁宏军 李兵 ZHAO Qiancheng;WANG Yan;LIANG Hongjun;LI Bing(Party Office and President's Office,Hunan University of Science and Technology,Xiangtan 411201,China;Logistics Department,Hunan University of Science and Technology,Xiangtan 411201,China)

机构地区：[1]湖南科技大学党办校办,湖南湘潭411100 [2]湖南科技大学后勤管理处,湖南湘潭411100

出　　处：《当代教育理论与实践》2023年第4期15-21,共7页Theory and Practice of Contemporary Education

摘　　要：高校家庭经济困难大学生的精准认定一直是高校资助工作中的难题,大数据分析为解决这一难题提供了方法论支撑。高校食堂的消费数据是大学生消费大数据的重要组成部分,利用大学生食堂消费大数据提升学生的精准化认定和资助,是当前一个热点。以湖南科技大学为例,利用大学生食堂就餐率和平均消费额数据进行统计分析,提出贫困大学生认定和资助基本方案,并以此为基础开展访谈与座谈调研,进行探究学生就餐率与就餐满意度关系的问卷调查,提出更加科学和精准的数据分析指标,建立食堂消费大数据分析的“决策树模型”,提升资助精准度。It is a tricky problem to accurately identify students with financial difficulties in colleges,but the big data has provided a methodological support for addressing this challenge.The data of the college students canteen consumption plays a necessary role in their consumption data.Currently,it is a heated topic to improve the accuracy of identifying students with financial difficulties and financial aid by using the big data of canteen consumption.Therefore,based on the identification and subsidization of impoverished college students reflected by the data of dining rate and average consumption amount,the paper takes Hunan University of Science and Technology as an example to carry out interviews and talks,as well as questionnaires on the relationship between the dining rate and satisfaction rate.In addition,the paper puts forward data analysis indicators and establishes“decision-making tree”model of big data of canteen consumption by analyzing the consumption data,financial aid data and survey data.

关 键 词：食堂消费 大数据 决策树 精准资助 

分 类 号：G47[文化科学—教育学]