设计学习技术:通过单一案例研究评估自闭症儿童的注意力

IF 2.9 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yussy Chinchay;César A. Collazos;Javier Gomez;Germán Montoro
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引用次数: 0

摘要

这项研究的重点是评估注意力,以确定自闭症儿童优化学习技术的设计需求。在一项包含基线、干预和干预后三个阶段的多基线设计的单一案例研究中,我们开发了一款支持个性化注意力策略的应用程序。我们对这些策略在数字学习任务中提高注意力能力的效果进行了评估。我们使用基于平板电脑的应用程序对儿童的互动体验、支持要求、任务完成时间和注意力模式进行了数据分析。研究结果有助于全面了解自闭症儿童如何参与数字学习活动,并强调了个性化注意力策略的重要性。研究还确定了关键的交互设计原则,以应对与注意力相关的挑战并促进学习体验的参与度。这项研究通过利用注意力评估,推动了自闭症谱系儿童包容性数字学习环境的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing Learning Technologies: Assessing Attention in Children With Autism Through a Single Case Study
This research focuses on the assessment of attention to identify the design needs for optimized learning technologies for children with autism. Within a single case study incorporating a multiple-baseline design involving baseline, intervention, and postintervention phases, we developed an application enabling personalized attention strategies. These strategies were assessed for their efficacy in enhancing attentional abilities during digital learning tasks. Data analysis of children's interaction experience, support requirements, task completion time, and attentional patterns was conducted using a tablet-based application. The findings contribute to a comprehensive understanding of how children with autism engage with digital learning activities and underscore the significance of personalized attention strategies. Key interaction design principles were identified to address attention-related challenges and promote engagement in the learning experience. This study advances the development of inclusive digital learning environments for children on the autism spectrum by leveraging attention assessment.
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来源期刊
IEEE Transactions on Learning Technologies
IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
7.50
自引率
5.40%
发文量
82
审稿时长
>12 weeks
期刊介绍: The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.
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