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CollectiAR: Computer Vision-Based Word Hunt for Children with Dyslexia

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Published:07 November 2022Publication History

ABSTRACT

Children with dyslexia face extra challenges in reading and writing words. They need more learning exercises than children with typical development to acquire vocabulary, which is often repetitive and daunting. Research has shown that combining visuospatial information in practices helped children with dyslexia memorize words, especially the real-world physical context. Nevertheless, the existing word recognition and spelling training games for children with dyslexia were not able to leverage children’s immediate vicinity. Therefore, we designed an augmented reality mobile game, CollectiAR, that uses computer vision to identify objects in the player’s immediate vicinity and direct the player to learn words for these objects. Our formative study with two elementary school teachers and a first-grade pupil found that CollectiAR has the potential to be an integral part of teachers’ instructional design and an engaging way for pupils to practice vocabulary exercises. Our teacher participants suggested that CollectiAR provide interfaces for teachers to participate in the game content design and computer vision model correction.

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      • Published in

        cover image ACM Conferences
        CHI PLAY '22: Extended Abstracts of the 2022 Annual Symposium on Computer-Human Interaction in Play
        November 2022
        419 pages
        ISBN:9781450392112
        DOI:10.1145/3505270

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        Publication History

        • Published: 7 November 2022

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