Vol 1, No 2 (2013)
Machine Learning Algorithms Used for Adaptive Modelling
Irena Nančovska Šerbec, Alenka Žerovnik, Jože Rugelj
Abstract
In the web-based system for assessment we use machine learning algorithms for modeling students’ knowledge. We applied clustering of students in similarity groups, attribute (or the most relevant exercises) selection and classification (of students in ability groups) on three different domains. The results of modeling are used for implementation of eassessment system that adapts to the students needs and knowledge. Decision trees, provide adaptive assessment useful in oral examination and examination of students with special needs. At the same time they provide teachers feedback about the students’ learning behavior during the course. From the student’s point of view, models provide quick self-examination. Based on the decision tree structure, student can get advice on how to improve his success rate. The same methodology could be used to model tourist’s holyday actiovities, based on his characteristics and preferrences.
Full text: 
PDF
Keywords
Adaptive modelling, e-learning, clustering, decission trees
Publication information
Volume 1, Issue 2
Year of Publication: 2013
ISSN: 1857 - 8721
Publisher: EDNOTERA
How to cite
Nančovska Šerbec I., Žerovnik A., Rugelj J.: Machine Learning Algorithms Used for Adaptive Modelling. Journal of Applied Economics and Business, Vol 1, No. 2, 5-12. (2013)