基于大学生学业的网络行为与特征模型

Network behavior and feature model based on college students’ learning situation

大学生是网络信息时代的主要受益者,他们的上网行为呈现出了很多特点,而不同的网络行为习惯会对学生的学习和生活产生不同的影响。为了更好地分析大学生上网行为和学生学业情况的关系,对不良学习情况进行预警,对二者关系进行了建模。首先,通过非参数检验选择与学生学业相关的上网行为变量;然后,利用二分类多元Logistic方程对网络行为与学生学业之间的内在关联进行建模。最后,通过模型分析网络行为与学生学业的因果关系,建立学业预警机制。使用所提模型可以对学生的上网行为进行积极引导,改善学生的网络行为结构,提升网络对其产生的积极影响。

College students benefit a lot from network information, and their network behavior has multiple features. Different network behavior habits have different effects on students’ learning and life. In order to better analyze the relationship between students network behavior and their learning situation to pre-warn the bad learning situation, a model between network behavior and learning situation was proposed. Firstly, some network behavior variables related to learning situation were selected through non-parametric tests. Then, a binary multivariate logistic regression model for the realtionship between network behavior and learning situation was constructed. Finally, with the causal relationship between network behavior and learning situation analyzed by the model, a pre-warning mechanism for the students’ learning situation was established. With the proposed model, students network behaviors are actively guided, structure of their network behavior is improved, and positive impact of the network on students is increased.