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Published in: Cluster Computing 3/2019

20-07-2017

Fuzzy based approach for adaptivity evaluation of web based open source Learning Management Systems

Authors: Farman Ali Khan, Faisal Shahzad, Muhammad Altaf

Published in: Cluster Computing | Special Issue 3/2019

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Abstract

Adaptive Learning Management System is a concept that has been recently explored to meet the individual needs of learners. Research studies regarding learning environments’, adaptation and personalization indicate that they play a key role to inspire, motivate and engage learners. The Learning Management Systems (LMSs) in this regard are currently facing the challenge of adapting the entire learning procedure according to the individual learning needs. Presently, there are numerous open source, custom developed, and commercial LMSs available. This paper presents an evaluation of web based open source LMSs since they can be easily supplemented and integrated with other software solutions than commercial and custom developed systems. The aim of this evaluation is to find a LMS platform that is most appropriate and has the potential for augmenting to an adaptive one. Initially, the evaluation is based on Elimination by Aspects approach for the qualification and selection of LMSs. Afterwards, the selected nine LMSs were evaluated using Linear Weighted approach (LWA) and fuzzy logic approach. The LWA was applied by assigning performance ratings to the overall categorical as well as adaptivity features. Finally the fuzzy logic was applied to the assigned ratings of each feature for the fuzzification of crisp set values. The results indicate that Moodle outperforms other platforms in overall functionally as well as in adaptation category.

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Metadata
Title
Fuzzy based approach for adaptivity evaluation of web based open source Learning Management Systems
Authors
Farman Ali Khan
Faisal Shahzad
Muhammad Altaf
Publication date
20-07-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1036-8

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