Adaptive Learning Content Based on Learning Styles in Learning Management System

2021 ◽  
pp. 3-11
Author(s):  
Lim Ean Heng ◽  
Phan Koo Yuen ◽  
Yong Tien Fui ◽  
Manoranjitham Muniandy ◽  
Anbuselvan Sangodiah ◽  
...  
Keyword(s):  
Learning Styles ◽  
Adaptive Learning ◽  
Management System ◽  
Learning Management System ◽  
Learning Content ◽  
Learning Management

Mining Student Learning Behavior and Self-assessment for Adaptive Learning Management System

2013 ◽  
pp. 70-79 ◽  
Author(s):  
Konstantina Moutafi ◽  
Paraskevi Vergeti ◽  
Christos Alexakos ◽  
Christos Dimitrakopoulos ◽  
Konstantinos Giotopoulos ◽  
...  
Keyword(s):  
Student Learning ◽  
Adaptive Learning ◽  
Management System ◽  
Learning Management System ◽  
Learning Behavior ◽  
Self Assessment ◽  
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 The patterns of accessing learning management system among students

2019 ◽  
Vol 13 (1) ◽  
pp. 15 ◽  
Author(s):  
Akibu Mahmoud Abdullahi ◽  
Mokhairi Makhtar ◽  
Suhailan Safie
Keyword(s):  
Management System ◽  
Assessment Tool ◽  
Learning Management System ◽  
Educational Data Mining ◽  
Learning Content ◽  
Student Access ◽  
The Mean ◽  
Learning Management ◽  
Educational Field ◽  
Online Software

<p>Learning Management System (LMS) is an online software that was hosted on a server and designed specifically to manage learners’ information, course registration, learning content, and assessment tool. Educational data mining is a way of evaluating and using methods for examining the unique and large dataset that come from educational field, and applying those in order to understand how students learn and the settings in which they learn. Many students use to miss some of the activities posted by their instructors, due to the short deadline, and they are not accessing the LMS regularly or every day. The purpose of this paper is to explore the way on how student access LMS and which day is the most frequent accessed. The findings show that, the total number of accessing LMS among 33 students is 16060, and the mean is 486.67, S16 recorded the highest number of accessing the LMS (965 access), while S24 as the least number of access (275). And the correlation between Tuesdays is significant, positive and strong correlation with Wednesdays (0.546), and positive, but weak with Thursdays (0.292), Fridays (0.244), Saturdays (0.334), and Sundays (0.291).</p>

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