scholarly journals Identifying learning styles and cognitive traits in a learning management system

Heliyon ◽  
2021 ◽  
pp. e07701
Author(s):  
Charles Lwande ◽  
Lawrence Muchemi ◽  
Robert Oboko
Keyword(s):  
Learning Styles ◽  
Management System ◽  
Learning Management System ◽  
Cognitive Traits ◽  
Learning Management

Design of an Adaptive Mobile Learning Management System

2008 ◽  
pp. 286-301 ◽  
Author(s):  
Hyungsung Park ◽  
Young Kyun Baek ◽  
David Gibson
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Mobile Learning ◽  
Management System ◽  
Learning Management System ◽  
Analysis Tool ◽  
User Interactions ◽  
E Learning ◽  
Adaptive Environment ◽  
Learning Management

This chapter introduces the application of an artificial intelligence technique to a mobile educational device in order to provide a learning management system platform that is adaptive to students’ learning styles. The key concepts of the adaptive mobile learning management system (AM-LMS) platform are outlined and explained. The AM-LMS provides an adaptive environment that continually sets a mobile device’s use of remote learning resources to the needs and requirements of individual learners. The platform identifies a user’s learning style based on an analysis tool provided by Felder & Soloman (2005) and updates the profile as the learner engages with e-learning content. A novel computational mechanism continuously provides interfaces specific to the user’s learning style and supports unique user interactions. The platform’s interfaces include strategies for learning activities, contents, menus, and supporting functions for learning through a mobile device.

Identification of Learning Styles in Distance Education Through the Interaction of the Student With a Learning Management System

2020 ◽  
Vol 15 (3) ◽  
pp. 148-160 ◽  
Author(s):  
Roberto Douglas da Costa ◽  
Gustavo Fontoura de Souza ◽  
Thales Barros de Castro ◽  
Ricardo Alexsandro de Medeiros Valentim ◽  
Aline de Pinho Dias
Keyword(s):  
Distance Education ◽  
Learning Styles ◽  
Management System ◽  
Learning Management System ◽  
Learning Management

scholarly journals A hybrid approach for supporting adaptivity in e-learning environments

2016 ◽  
Vol 33 (5) ◽  
pp. 333-348 ◽  
Author(s):  
Mohammad Al-Omari ◽  
Jenny Carter ◽  
Francisco Chiclana
Keyword(s):  
Learning Styles ◽  
Learning Environments ◽  
Intelligent Agents ◽  
Management System ◽  
Learning Management System ◽  
Hybrid Approach ◽  
Content Type ◽  
E Learning ◽  
Learning Management ◽  
System Prototype

Purpose The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity in any given learning management system based on learners’ learning styles. Design/methodology/approach This paper offers a brief review of current frameworks and systems to support adaptivity in e-learning environments. A framework to support adaptivity is designed and discussed, reflecting the hybrid approach in detail. A system prototype is developed incorporating different adaptive features based on the Felder-Silverman learning styles model. Finally, the prototype is implemented in Moodle. Findings The system prototype supports real-time adaptivity in any given learning management system based on learners’ learning styles. It can deal with any type of content provided by course designers and instructors in the learning management system. Moreover, it can support adaptivity at both course and learner levels. Originality/value To the best of the authors’ knowledge, no previous work has been done incorporating the concept of the ECA model and intelligent agents as hybrid architecture to support adaptivity in e-learning environments. The system prototype has wider applicability and can be adapted to support different types of adaptivity.

scholarly journals Examining the use of a Personalized Learning Management System (PLMS) to Increase Student Engaagement in High School Physics

2018 ◽  
Author(s):  
Meera Singh
Keyword(s):  
Student Engagement ◽  
Learning Styles ◽  
Survey Data ◽  
Learning Style ◽  
Management System ◽  
Learning Management System ◽  
Project Based Learning ◽  
Digital Learning ◽  
Learning Management ◽  
K 12

Motivated by the drive to impact the quality and diversity of students applying to engineering schools, this study evaluates a component of a Personalized Digital Learning Management System (PLMS) that has been designed to increase student engagement in K-12 Physics. In particular, a non-traditional project based learning module, with roots in game-based learning, has been developed and executed in grade 8 science classrooms. Pre and post survey data that includes attitudinal markers, learning style profiles, gender, and assessments of knowledge gained, are analyzed and presented. Results suggest that students who are more interested in science, physics and engineering tend to have learning styles that require programming that is more active and less sequential than traditionally delivered. This is particularly the case for female students. The non-traditional game based project acted to provide these types of learning opportunities and post survey data showed a very high level of student engagement. Results obtained will be used to further refine the PLMS.

A Novel E-Learning Management System for Appropriate Recommendations on the Learning Contents

2015 ◽  
pp. 16-45 ◽  
Author(s):  
Jegatha Deborah Lazarus ◽  
Baskaran Ramachandran ◽  
Kannan Arputharaj
Keyword(s):  
Performance Evaluation ◽  
Learning Styles ◽  
Management System ◽  
Learning Management System ◽  
Ontology Alignment ◽  
Ontology Construction ◽  
E Learning ◽  
Learning Management ◽  
And Performance ◽  
Technological Constraints

Educational organizations are able to bridge organizational gaps due to the rapid advances in science and technology. Specifically, e-learning drastically reduces the learning time compared to the traditional classroom setting. The challenges in e-learning are the organization of learning contents, characteristics of the learning individual, technological constraints, and performance evaluation. Moreover, the success of the e-learning environment is greatly influenced by the factors like appropriate recommendations of learning contents, content delivery, performance evaluation, and the maintenance of the psychological level through identification of the learning styles of the learners. The continual process of performance evaluation is commonly attributed by the challenging issues of Ontology Construction and Alignment in order to enhance the semantics of the evaluation documents. In the rest of the chapter, a novel rule-based e-learning management system is discussed as a solution for appropriate recommendations of the learning contents based on the psychological understanding of the learners for learning using fuzzy logic and the subsequent evaluation of the learners using Ontology Construction and Ontology Alignment technique using deontic logic. The experiments have been carried out on evaluating the learning of C programming language using an e-learning framework.

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