Tendency of Educational Data Mining in
Digital Learning Platform
Volume 2 - Issue 1
Gajendra Sharma*
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- Department of Computer Science & Engineering, Kathmandu University (KU), Nepal
*Corresponding author:
Gajendra Sharma, Department of Computer Science & Engineering, Kathmandu University (KU), Nepal
Received: October 24, 2020; Published: November 02, 2020
DOI:
10.32474/CTCSA.2020.02.000127
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Abstract
With the advancement of technology learning process have been more reachable and interactive like never before. Till the date
many online learning platforms have been introduced. The platforms with constant improvisation in teaching-learning technique
have been able to sustain. For improvisation there need constant analysis of the data and implement the suggested changes are
required. The analysis of the educational data is using data mining techniques is called Educational data mining. EDM helps to
discover the patterns of learning behavior hidden in the data sets. This research paper aimed to do a review of different other papers
which were based on EDM in online learning environment. It has been seen that most paper used classification and clustering as
their data mining technique. K-means clustering has been used as cluster analysis technique for exploring the dataset. Similarly,
Weka tools had been found to be used as data mining software. Future recommendations in EDM are presented in terms of future
scope of the researches related to it to make the researches more trustworthy.
Keywords: Data mining; Educational data mining; Online learning; E-learning; Classification; Clustering; K-Means clustering
Abstract|
Introduction|
Literature Review|
Research Problem|
Findings from Literature Review|
Conclusion|
Future Scope and Recommendation|
References|