Recognition and Analysis of Poor Students on College Students Campus Card Consumption Data Based on Big Data

DOI

10.2991/icmeit-17.2017.21How to use a DOI?

Keywords

Big data, Campus card, Poor student recognition, Consumption data

Abstract

Subsidization for students from low-income families is a major student management work for colleges and universities. With deep and extensive use of big data in all sectors, relevant big data shall be used to identify poor students. Using big data rationally for targeted subsidization represents in-depth application of big data in educational field. In this thesis, the researchers collected 36546 data concerning dining consumption of students in three months, used Datist, a big data analysis software to build a model, acquired concerning dining habits, consuming behaviors, situations in school and consumption indicators of the students, and then selected poor students. This study laid a solid foundation for large-scale dynamic implementation of "campus big data and targeted subsidization", accurate recognition of poor students and rational student analysis in future.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Aifeng Li
AU  - Zhineng Xiao
AU  - Biyun Liang
PY  - 2017/05
DA  - 2017/05
TI  - Recognition and Analysis of Poor Students on College Students Campus Card Consumption Data Based on Big Data
BT  - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)
PB  - Atlantis Press
SP  - 111
EP  - 114
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-17.2017.21
DO  - 10.2991/icmeit-17.2017.21
ID  - Li2017/05
ER  -