A Framework for Automatic Identification of Learning Styles in Learning Management Systems

Abstract

A current concern of modern societies is the quality of their educational systems. Learning Management Systems (LMSs) are technological tools that have been used to improve and extend the traditional educational system. Although LMSs have greatly benefited from technological advances, this type of educational platforms are still in need of mechanisms to provide virtual educational environments in which students are considered the main actor in the design of the learning process, thus contributing to increase the quality of educational systems. In particular, LMSs usually lack mechanisms for recognizing users' learning styles, which describe the way a learner acquires and process information.In this work we propose a framework for automatic identification of learning styles in LMSs and present a specific implementation. A key goal of the framework design is to provide researchers and practitioners with a tool that facilitates the specification of expert knowledge for classifying students with respect to their learning styles in LMSs.

Designing an expert system for determining student learning styles using forward chaining in engineering education

“…Engineering education in the learning process also certainly has the uniqueness of learning style (Larkin-Hein, & Budny, 2001). This learning style can be predicted with a specific application design through the Expert System (Movafegh Márquez et al, 2015;Ozdemir et al, 2016;Marlinda, Saputra, & Indrarti, 2019;Sakaan, & abdel-wahab, 2021), one of them is by the forward chaining method. The system discussion is the implementation of a process that translates the design results into the form of software in full (Ekayani, 2017).…”