Exploring Student Engagement in Online Programming Courses: A Two-Level K-means Analysis
Author:
Affiliation:
1. University of Zadar,Department of Information,Zadar,Croatia
2. University of Split,Sciences Faculty of Science,Split,Croatia
Funder
Office of Naval Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10271384/10271386/10271619.pdf?arnumber=10271619
Reference32 articles.
1. Classifying learner engagement through integration of multiple data sources;beal;Proceedings of the 21st national conference on Artificial intelligence – Volume 1,2006
2. Educational Data Mining and Learning Analytics
3. An Approach of Improving Student’s Academic Performance by using K-means clustering algorithm and Decision tree;shovoni;International Journal of Advanced Computer Science and Applications(IJACSA),2012
4. Scikit-learn: Machine Learning in Python;pedregosa;J Ournal of Machine Learning Research,2011
5. Student Engagement Level in an e-Learning Environment: Clustering Using K-means
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