大数据视角下高校本科生学业问题相关因素分析与研究

Wenxian Bian, Yongming Yao, Yang Cao
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摘要

为了解决传统学业预警系统的滞后性和被动性,我们通过收集学生学业大数据,从学校、家庭、社会和学生自身四个维度分析学生学业问题的相关因素。建立大数据平台,设计基于大数据平台的学生学习支持机制,实现预防性管理、后续教育、针对性支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis and Research on the Related Factors of Academic Problems of University Undergraduates from the Perspective of Big Data
In order to solve the lag and passiveness of the traditional academic early warning system, through the collection of students’ academic big data, we analyze the related factors of students’ academic problems from the four dimensions of school, family, society and students themselves. We established a big data platform and designed a student learning support mechanism based on the big data platform, in order to achieve preventive management, follow-up education, and targeted support.
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