Abstract—Learning is a kind of important human behavior to
acquire knowledge. This paper discussed temporal
characteristics of network course learning on behavior
dynamics. Firstly, the students behavior data of the network
course learning for 8-weeks are collected from online learning
platform. Then, the work used the Maximum Likelihood
Estimation(MLE) method for estimating the power exponent of
learning behavior interval time distribution, and introduced
Kolmogorov-Smirnov(KS) method to test power-law
hypothesis .The empirical research results show that: both in the
group and individual level, learning behavior time interval obey
characteristics of power-law distribution. Underlying these,
This thesis combined with the learning psychology, environment
and other factors explained the statistical characteristics, and
provided some suggestions for teaching management.
Index Terms—Empirical research, behavior dynamics, behavior interval time distribution, power-law.
Yan Cheng is with Tongji University. She is also with Jiangxi Normal University, Nanchang, Jiangxi, China (e-mail: email@example.com).
Yan Zeng is with Jiangxi Normal University, Nanchang, Jiangxi, China (e-mail: firstname.lastname@example.org).
Cite: Yan Cheng and Yan Zeng, "An Empirical Research of Human Behavior Dynamics in Network Course Learning," International Journal of Information and Education Technology vol. 7, no. 1, pp. 6-10, 2017.