Application of multiple criteria decision methods to optimise learning scenarios
Articles
Julija Kurilova
Vilniaus universitetas
Eugenijus Kurilovas
Vilniaus Gedimino technikos universitetas
Published 2016-12-20
https://doi.org/10.15388/LMR.B.2016.10
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Keywords

learning scenarios
fuzzy numbers
Analytic Hierarchy Process
optimisation
multiple criteria decision analysis
expert evaluation
learning components

How to Cite

Kurilova J. and Kurilovas E. (2016) “Application of multiple criteria decision methods to optimise learning scenarios”, Lietuvos matematikos rinkinys, 57(B), pp. 55–59. doi: 10.15388/LMR.B.2016.10.

Abstract

In the paper, learning scenarios (units) quality evaluation and optimisation problems are analysed. Learning scenarios optimisation is referred here as its personalisation according to learners needs. In the paper, comparative analysis of two popular optimisation methods based on Fuzzy numbers theory and Analytic Hierarchy Process is performed, aiming to measure what method is the most suitable to evaluate the quality of personalised learning scenarios. Learning scenarios quality is referred here as its suitability to learners needs. Research results show that Fuzzy numbers theorybased methods are more suitable to evaluate the quality of personalised learning scenarios.

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