Adaptation algorithms for selecting personalised learning experience based on learning style and dyslexia type
| DOI | https://doi.org/10.1108/DTA-10-2018-0092 |
| Pages | 189-200 |
| Published date | 01 April 2019 |
| Date | 01 April 2019 |
| Author | Aisha Yaquob Alsobhi,Khaled Hamed Alyoubi |
| Subject Matter | Library & information science |
Adaptation algorithms for
selecting personalised learning
experience based on learning
style and dyslexia type
Aisha Yaquob Alsobhi and Khaled Hamed Alyoubi
Department of Computing and Information Technology,
King Abdulaziz University, Jeddah, Saudi Arabia
Abstract
Purpose –Through harnessing the benefits of the internet, e-learning systems provide flexible learning
opportunities that can be delivered at a fixed cost at a time and place to suit the user. As such, e-learning
systems can allow students to learn at their own pace while also being suitable for both distance and
classroom-based learning activities. Adaptive educational hypermedia systems are e-learning systems that
employ artificial intelligence. They deliver personalised online learning interventions that extend electronic
learning experiences beyond a mere computerised book through the use of intelligence that adapts the content
presented to a user according to a range of factors including individual needs, learning styles and existing
knowledge. The purpose of this paper is to describe a novel adaptive e-learning system called dyslexia
adaptive e-learning management system (DAELMS). For the purpose of this paper, the term DAELMS will be
employed to describe the overall e-learning system that incorporates the required functionality to adapt to
students’learning styles and dyslexia type.
Design/methodology/approach –The DAELMS is a complex system that will require a significant
amount of time and expertise in knowledge engineering and formatting (i.e. dyslexia type, learning styles,
domain knowledge) to develop. One of the most effective methods of approaching this complex task is to
formalise the development of a DAELMS that can be applied to different learning styles models and
education domains. Four distinct phases of development are proposed for creating the DAELMS. In this
paper, we will discuss Phase 3 which is the implementation and some adaption algorithms while in future
papers will discuss the other phases.
Findings –An experimental study was conducted to validate the proposed generic methodology and the
architecture of the DAELMS. The system has been evaluated by group of university students studying a
Computer Science related majors. The evaluation results proves that when the system provide the user with
learning materials matches their learning style or dyslexia type it enhances their learning outcomes.
Originality/value –The DAELMS correlates each given dyslexia type with its associated preferred learning
style and subsequently adapts the learning material presented to the student. The DAELMS represents an
adaptive e-learning system that incorporates several personalisation options including navigation, structure
of curriculum, presentation, guidance and assistive technologies that are designed to ensure the learning
experience is directly aligned with the user’s dyslexia type and associated preferred learning style.
Keywords E-learning, Personalised learning, Learning style, Dyslexia, Adaptive e-learning,
Recommendation algorithm
Paper type Research paper
Introduction
In recent years, more and more researchers have attempted to develop an understanding of
how technology can enhance the effectiveness of teaching and learning interventions (Wang
et al., 2017). E-learning has evolved into a key tool that can facilitate and enhance the
progression of student’s knowledge, skills and understanding (Nuttal, 2014). The web, in
particular, has gained increasing importance as a teaching tool and is more and more
frequently employed within contemporary classrooms (Edyburn, 2015). While it is readily
acknowledged that technology can positively facilitate a teacher’s ability to deliver the key
elements of the curriculum, the interventions that are currently utilised in classrooms often
fail to take into consideration the needs and behaviours of students with disabilities.
Data Technologies and
Applications
Vol. 53 No. 2, 2019
pp. 189-200
© Emerald PublishingLimited
2514-9288
DOI 10.1108/DTA-10-2018-0092
Received 16 October 2018
Revised 10 February 2019
Accepted 23 February 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2514-9288.htm
189
Learning
experience
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