文章基本信息

标题：A Predictive Model to Evaluate Students’ Cognitive Engagement in Online Learning
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作者：Nurbiha A. Shukor ; Nurbiha A. Shukor ; Zaidatun Tasir 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2014
卷号：116
页码：4844-4853
DOI：10.1016/j.sbspro.2014.01.1036
语种：English
出版社：Elsevier
摘要：The expanding usage of online learning at all levels of education has drawn attention to the quality of online learning. In this study, online learning quality is evaluated through students’ cognitive engagement which is reflected in their online written messages in discussions and their online participation. This study proposes the use of two types of data: students’ participation, and written messages. Both types of data was collected and analyzed using the data mining technique to produce a predictive model that illustrates students’ pathways while engaging in online learning cognitively. The findings of this study indicate that from 22 variables, only two were significant for students’ online cognitive engagement; sharing information and posting high- level messages. The two variables led to the formation of three different pathways in the students’ predictive model.
关键词：Online learning;cognitve engagement;content analysis;data mining