Mobile cloud computing: An effective multimodal interface tool for students with dyslexia
The explosive growth of mobile technology and developments in cloud computing have provided new and powerful possibilities for mobile learning (m-learning). M-learning, which is an influential trend in the educational process, promotes learning accessibility and flexibility for a substantial and val...
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Published in: | Computers in human behavior Vol. 75; pp. 160 - 166 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Elmsford
Elsevier Ltd
01-10-2017
Elsevier Science Ltd |
Subjects: | |
Online Access: | Get full text |
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Summary: | The explosive growth of mobile technology and developments in cloud computing have provided new and powerful possibilities for mobile learning (m-learning). M-learning, which is an influential trend in the educational process, promotes learning accessibility and flexibility for a substantial and valuable segment of society: students with dyslexia. Although there is a substantial amount of research that discusses the use of m-learning by students with dyslexia, there are many gaps that must still be addressed. One substantial issue pertains to the lack of an effective, multimodal, human–computer user interface m-learning tool that combines different input and output modes based on each student's learning style. In this paper, the authors develop a novel, interactive, multimodal interfaced, cloud-based m-learning tool with which students can naturally interact based on their preferred learning styles. This multimodal interface tool enhances the learning capabilities of students with dyslexia by almost 30% by customizing their multimodal functionality to meet their learning needs.
•A multimodal, cloud-based m-learning tool for promoting dyslexia is proposed.•The tool relies on standard educational strategies, which are implemented in SA.•Customizing the multimodal functionality to meet dyslexic students' learning needs.•Dyslexic students' Learning capabilities are enhanced by almost 30% using the tool. |
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ISSN: | 0747-5632 1873-7692 |
DOI: | 10.1016/j.chb.2017.05.014 |