NDLI: An Empirical Case Study of Internet Usage on Student Performance based on Fuzzy Association Rules

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An Empirical Case Study of Internet Usage on Student Performance based on Fuzzy Association Rules

Content Provider	ACM Digital Library
Author	Huang, Chih-Hong Lien, Hsing-Lung Wang, Leon Shyue-Liang
Abstract	A learning management system (LMS) gathers an amount of data about the progress of student learning, demographic and students' back-ground over different sessions. Teachers are very concerned about the unknown relationships among a hundred variables about students in a LMS for adjusting their teaching strategies and pedagogies. However, teachers are not satisfied with the traditional statistical reports, which are explored with limited relative variables on the issue of learning achievement in static sessions. The data from LMS also can combine with the data of network behavior. In NUK, students living in the dormitory are not allowed to transmit mass data. The dormitory internet management system of NUK have flow limitation. The daily transmission of the individual IP address shall not exceed 4GB/day. We have observed that some student usually over-flow his network limitation, because of they are addicted to online games or peer-to-peer software. Thus, we have an inference about that: 'student spend a lot of time on surfing, playing or downloading, will got low learning achievements'. Therefore, to address this issue, we propose a novel mining model, Flow-Mining model, to detect the correlation in student learning performance, characteristics and network flow.
Starting Page	1
Ending Page	5
Page Count	5
File Format	PDF
ISBN	9781450341295
DOI	10.1145/2955129.2955132
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-15
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Higher education Network analysis Association rules Data mining
Content Type	Text
Resource Type	Article

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