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Vehicle Detection Using Alex Net and Faster R-CNN Deep Learning Models: A Comparative Study Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Data-Driven Iterative-Evolution-Participatory Design Model on Motion-Based Science Educational Application for ADHD Learners

Authors : Ahmad Fazil Zainal, Halimah Badioze Zaman

Published in: Advances in Visual Informatics

Publisher: Springer International Publishing

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Abstract

Attention Deficit Hyperactivity Disorder (ADHD) learners are identified as having problems in learning due to their distinctive characteristics of hyperactivity and inability to give attention to learning. Gamification technology, especially motion-based gamification application, specifically designed for ADHD learners can have significant promise for individuals with ADHD. This paper focuses on the data-driven iterative design adopted on the development of the motion-based science educational application for ADHD learners (Sains-4SL) and its evaluation based on the effectiveness construct of this motion-based science educational application. The effectiveness of this motion-based science educational application was measured based various indicators such as: its learnability, students’ attitude towards the application; and the science literacy aspects of the students after experiencing using the application. The data-driven iterative-participatory design approach which underwent many rounds of iterations, was found to be effective in the design and development of the application as these iterations, contributed to a more accurate specification requirements for the ADHD learners. The evaluation conducted found that the motion-based science educational application (Sains-4SL) was positively effective in supporting ADHD learners learn science.

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Metadata
Title
Data-Driven Iterative-Evolution-Participatory Design Model on Motion-Based Science Educational Application for ADHD Learners
Authors
Ahmad Fazil Zainal
Halimah Badioze Zaman
Copyright Year
2017
Book
Advances in Visual Informatics

Print ISBN: 978-3-319-70009-0

Electronic ISBN: 978-3-319-70010-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-70010-6_19

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