International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 9, No. 2, 8 Mar. 2019
Cover page and Table of Contents: PDF (size: 324KB)
Identification of Influencing Factors for Enhancing Online Learning Usage Model: Evidence from an Indian University
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Author(s)
Sachin Ahuja
1,*
Puninder Kaur
1
S N Panda
1
Index Terms
Online Course, Online Learning, Data Mining, Academic Performance
Abstract
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.
Cite This Paper
Sachin Ahuja, Puninder Kaur, S N Panda,"Identification of Influencing Factors for Enhancing Online Learning Usage Model: Evidence from an Indian University", International Journal of Education and Management Engineering(IJEME), Vol.9, No.2, pp.15-24, 2019. DOI: 10.5815/ijeme.2019.02.02
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