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

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Advances in Visual Informatics (IVIC 2017)

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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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Correspondence to Halimah Badioze Zaman .

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Zainal, A.F., Zaman, H.B. (2017). Data-Driven Iterative-Evolution-Participatory Design Model on Motion-Based Science Educational Application for ADHD Learners. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2017. Lecture Notes in Computer Science(), vol 10645. Springer, Cham. https://doi.org/10.1007/978-3-319-70010-6_19

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

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