Abstract
Digital technologies are an essential resource for maximizing education opportunities, yet the COVID-19 pandemic has exposed learning inequities, particularly among underrepresented groups such as children with autism. In this study, we have evaluated the quality of a distinctive dataset of multiplatform software applications, encompassing both assistive and mainstream software, first-hand acquired from special education professionals and families of children with autism. Through a heuristic evaluation based on a system indicators, and an in-depth analysis, we aimed to (1) assess the quality and effectiveness of assistive technologies in supporting the education of children with autism; (2) determine the adaptability of mainstream applications to the unique educational needs of children with autism; and (3) explore the features and constraints of applications targeting children with ASD, categorized according to the needs they cover. The resulting quality ranking, organized by cognitive domains, provides insights into the engagement and effectiveness of applications supporting the learning of children with autism. Furthermore, the findings delineating the functionalities and limitations of these applications contribute to the identification of necessary software engineering best practices. These practices align with user-centered design principles and drive the development of accessible software, thereby fostering high-quality inclusive education for children with autism.
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