Mining learners’ behavior in accessing web-based interface

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.