文章基本信息

标题：Identification of Influencing Factors for Enhancing Online Learning Usage Model: Evidence from an Indian University
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作者：Sachin Ahuja ; Puninder Kaur ; S N Panda 等
期刊名称：International Journal of Education and Management Engineering(IJEME)
印刷版ISSN：2305-3623
电子版ISSN：2305-8463
出版年度：2019
卷号：9
期号：2
页码：15-24
DOI：10.5815/ijeme.2019.02.02
出版社：MECS Publisher
摘要：With advent of technology online education has become the core of educational settings worldwide. This paper aims to identify the factors that contribute in enhancing the online learning usage model in context of India, an emerging leader in Educational settings across the globe. In this study, data mining techniques were applied on the data collected from the log files of online courses. The initial investigations supported the use of custom build framework for teaching online courses. Data Structure course was taught using online platform and the data was collected using the log files. The data collected was further analysed using data mining techniques using Rapid miner tool. Although the results from three different data mining techniques showed some variations but the inferences from the results identified few common factors that have influence on enhancing the online learning usage model. Clustering techniques revealed that factors related to timely checking of online contents and posting have positive impact on online learning however decision trees supported that timely completing the online assignments along with checking of online contents and posting of messages played an important role in terms of enhancing the academic performance. This paper identifies three factors for teachers teaching online courses to improve overall performance of the students by learning from Indian University Success.
关键词：Online Course;Online Learning;Data Mining;Academic Performance