Dijana Oreški, Goran Hajdin, "Development and Comparison of Predictive Models based on Learning Management System Data," WSEAS Transactions on Information Science and Applications, vol. 16, pp. 192-201, 2019, DOI:
Dijana Oreški, Goran Hajdin. Development and Comparison of Predictive Models based on Learning Management System Data.
WSEAS Transactions on Information Science and Applications. 2019;16:192-201.
WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 16, 2019
Development and Comparison of Predictive Models based on Learning Management System Data
Authors: ,
Abstract: This study introduces and evaluates different feature reduction and supervised machine learning approaches to predict the students` academic success. Our analysis is based on data about students` activities in the learning management system. We found that neural networks based approach with principal component analysis in feature reduction is the most effective for learning management system data.
Keywords:
data preparation, feature reduction, machine learning, neural networks, academic performance, student success.
Pages: 192-201 WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 16, 2019, Art. #22 DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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