How Surfing Habits Affect Academic Performance: An Experimental Study
The issues regarding relationships between surfing habits and academic performance of university students have attracted much attention of all kinds of research communities. The approaches of statistical analysis and data mining with imperfect datasets are used in previous works. In this paper, an experimental study about the relationships between surfing habits and academic performance is conducted. Particularly, we observe a surprising results on extensive datasets, which contains the information of students, e.g. basic profiles, Internet using logs and course scores. First, several statistical methods are used to find the associations between students' surfing habits and academic performance. Then, a learning algorithm is devised to cluster the students according to their different surfing habits. Furthermore, we develop a BP neural network to predict the rate of failing a test of a student based on his/her basic information, surfing habits and the clustering information. According to the aforementioned approaches, we find an interesting result that the academic performance of students in universities is quite possibly enhanced if the network connections are always terminated at 24:00 p.m.
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