Web Usage Mining to Evaluate the Transfer of Learning in a Web-Based Learning Environment

F. Chanchary, Indrani Haque, M. Khalid
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引用次数: 35

Abstract

Application of data mining for web log analysis has received significant attention in finding customers' behavioral pattern in e-commerce and learners' behavioral pattern in e- learning. While hit-counts indicate customers' interest in the product or purchasing behavior, a student's visits to a Learning Management System (LMS) do not necessarily involve transfer of learning. Addressing such complexity in e-learning, this study analyzed students' log of a Learning Management System (LMS) of two subjects at a university in Bangladesh, taught over six weeks duration. Data mining and statistical tools have been used to find relationships between students' LMS access behavior and overall performances. Results show that students having 'Low' access obtained poor grade, on campus access was higher than access from home. Background of students is very important for effective usage of web resources. Majority of the student considered LMS to be a quite helpful tool as teaching-learning method. Preparation and cleaning of the web-log files as well as application of data mining algorithms is important for learners' web usage analysis.
基于Web的学习环境中评估学习迁移的网络使用挖掘
将数据挖掘技术应用于网络日志分析,在电子商务中发现客户的行为模式,在电子学习中发现学习者的行为模式等方面受到了广泛的关注。虽然点击次数表明客户对产品的兴趣或购买行为,但学生访问学习管理系统(LMS)并不一定涉及学习转移。针对电子学习的这种复杂性,本研究分析了孟加拉国一所大学两门学科的学生学习管理系统(LMS)的日志,教学时间超过六周。数据挖掘和统计工具已经被用来发现学生的LMS访问行为和整体表现之间的关系。结果表明,“低”访问的学生成绩较差,校园访问高于家庭访问。学生的背景对网络资源的有效利用非常重要。大多数学生认为LMS是一种非常有用的教学工具。网络日志文件的准备和清理以及数据挖掘算法的应用对学习者的网络使用分析非常重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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