The Impact of Adaptation Based on Students' Dyslexia Type: An Empirical Evaluation of Students' Satisfaction

Al-Dawsari

HCI in Games: Serious and Immersive Games

2021

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Section: Discussionsupporting

confidence: 91%

Section: Related Workmentioning

confidence: 99%

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Understanding the Impact on Learners’ Reading Performance and Behaviour of Matching E-Learning Material to Dyslexia Type and Reading Skill Level

Al-Dawsari

HCI in Games: Serious and Immersive Games

2021

Self Cite

“…These limitations include a lack of interactivity, of learner control of the environment, of adaptive presentation formats, of learning navigation and of personalisation of educational materials. From this perspective, contextualising learning serves as a new paradigm for adaptive e-learning systems, which aims to solve these traditional limitations (Alghabban and Hendley 2020b). A system's ability to adjust its output in response to learner needs is often referred to as adaptivity or adaptation (Brusilovsky 2001).…”

Section: Introductionmentioning

confidence: 99%

“…dyslexia) by considering their characteristics within an educational environment. For learners with dyslexia, characteristics such as their dyslexia type and their knowledge level are significant factors influencing their learning (Benmarrakchi et al 2017b;Alghabban and Hendley 2020b). These can be incorporated into the learning environment to drive the personalisation of the learning experience.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Effectiveness of Adaptation Based on Dyslexia Type and Reading Skill Level to Support Learners with Dyslexia

Electronic Workshops in Computing

2022

E-learning has become a popular tool for helping people with dyslexia to improve their reading, as it provides interactivity anywhere and at any time. However, most traditional e-learning systems are designed for a generic learner, regardless of each individual's differences and needs. In this context, a successful e-learning system needs to consider the learner's individual characteristics -in particular, their dyslexia type and reading skill level. This can lead to a more appropriate learning experience and interaction. There is, however, a need to understand the value of this adaptation, particularly on the learning gain. This study contributes to research by bridging this under-investigated gap by evaluating the learning effectiveness of adapting material based on the learner's dyslexia type and reading skill. A controlled, between-subjects experiment with 47 subjects is described and the results presented and analysed. The findings indicate that adaptation based on the combination of dyslexia type and reading skill level results in significantly better short-term and long-term learning gains and greater learner satisfaction than non-adapted material. There is also evidence that this benefit transfers to learners' reading performance on unseen material.

Perceived Level of Usability as an Evaluation Metric in Adaptive E-learning

2022

SN COMPUT. SCI.

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The global spread of COVID-19 has shifted the learning process towards e-learning. In this context, a critical challenge for researchers is to understand and evaluate the effectiveness of e-learning, especially when the learning is adapted to the needs of individual users. In this work we argue that the learner’s perception of the level of usability of a system is a valuable metric that gives an insight into the learners’ engagement and motivation to learn. Little attention has been paid to this metric. In this paper we explore why this is important and valuable. We present a case study which uses the System Usability Scale (SUS) questionnaire to measure the user’s perception of usability as an indirect (proxy) measure of engagement. A between-subject experiment was conducted with 41 learners with dyslexia. The intervention group used the adaptive version of the e-learning system that matched the material to the needs of the learner. The control group used a standard version. At the end, learning gain and SUS scores were assessed. The correlation between learning performance and the perceived level of usability was positive and moderate (0.517, p < 0.05) among participants in the intervention group. However, learning performance and perceived level of usability were unrelated in the control group (− 0.364, p > 0.05). From this, and other work, it appears that using a learner’s assessment of the usability of a system is an effective way to measure their attitude to their learning. It reflects their perception of its suitability to their needs and this, in turn, is likely to affect their engagement and motivation. As such, this provides an effective instrument to judge whether adaptation based on learner needs has been successful.