Educational Customization by Homogenous Grouping of e-Learners based on their Learning Styles
Mohammadreza amiri, GholamAli montazer, Ebrahim Mousavi

TL;DR
This paper presents a method for customizing e-learning environments by grouping learners based on their learning styles using the Felder-Silverman model and Fuzzy Set Theory, leading to improved educational outcomes.
Contribution
It introduces a novel grouping approach combining learning styles and Fuzzy Set Theory to enhance personalization and effectiveness in e-learning systems.
Findings
Experimental group scored higher in educational success
Experimental group showed greater educational satisfaction
Grouping method improved learning outcomes
Abstract
The E-learning environment offers greater flexibility compared to face-to-face interactions, allowing for adapting educational content to meet learners' individual needs and abilities through personalization and customization of e-content and the educational process. Despite the advantages of this approach, customizing the learning environment can reduce the costs of tutoring systems for similar learners by utilizing the same content and process for co-like learning groups. Various indicators for grouping learners exist, but many of them are conceptual, uncertain, and subject to change over time. In this article, we propose using the Felder-Silverman model, which is based on learning styles, to group similar learners. Additionally, we model the behaviors and actions of e-learners in a network environment using Fuzzy Set Theory (FST). After identifying the learning styles of the…
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Taxonomy
TopicsLearning Styles and Cognitive Differences · Educational Technology and Assessment
MethodsSparse Evolutionary Training
