Designing Learning Technologies: Assessing Attention in Children With Autism Through a Single Case Study

Abstract

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.