Please use this identifier to cite or link to this item:
Title: Mining learners’ behavior in accessing web-based interface
Authors: Lee, MW
Chen, SY
Liu, X
Keywords: Cognitive styles;Web-based learning;Web-based interface;Data mining;Classification and regression tree
Issue Date: 2007
Publisher: Springer
Citation: In Hui, KC (ed). Technologies for E-Learning and Digital Entertainment. Heidelberg: Springer, 2007
Abstract: Web-based technology has already been adopted as a tool to support teaching and learning in higher education. One criterion affecting the usability of such a technology is the design of web-based interface (WBI) within web-based learning programs. How different users access the WBIs has been investigated by several studies, which mainly analyze the collected data using statistical methods. In this paper, we propose to analyze users’ learning behavior using Data Mining (DM) techniques. Findings in our study show that learners with different cognitive styles seem to have various learning preferences, and DM is an efficient tool to analyze the behavior of different cognitive style groups.
ISBN: 978-3-540-73010-1
ISSN: 1611-3349
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Article_info.txt234 BTextView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.