集合:计算机视觉为基础的单词搜索儿童阅读障碍

Danlu Fei, Ze-Feng Gao, Linping Yuan, Z. Wen
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引用次数: 1

摘要

患有阅读障碍的儿童在阅读和书写单词方面面临额外的挑战。与正常发育的儿童相比,他们需要更多的学习练习来获得词汇,这些练习往往是重复的,令人生畏的。研究表明,在练习中结合视觉空间信息有助于有阅读障碍的儿童记忆单词,尤其是现实世界的物理环境。然而,现有的单词识别和拼写训练游戏无法利用儿童的直接邻近。因此,我们设计了一款增强现实手机游戏《CollectiAR》,它使用计算机视觉来识别玩家附近的物体,并指导玩家学习这些物体的单词。我们对两名小学教师和一名一年级学生的形成性研究发现,CollectiAR有潜力成为教师教学设计的一个组成部分,并成为学生练习词汇练习的一种有吸引力的方式。我们的教师参与者建议CollectiAR为教师提供参与游戏内容设计和计算机视觉模型校正的接口。
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CollectiAR: Computer Vision-Based Word Hunt for Children with Dyslexia
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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