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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that can impair, to some extent, communication, socialization and also present stereotyped and restricted behaviors. The objective of this article was to present test results from the ACA (Learning with Alternative Communication) application, which uses the images of the Daily Life Activities to teach naming of objects, alphabet, syllables, and words, and to verify if there was vocabulary gain and literacy aid growth, as well as its usability and gamification issues. The tests were carried out with 28 children diagnosed with mild and moderate ASD. The results showed that such App is effective in its performance, since children have gained vocabulary.Resumo. Transtorno do Espectro Autismo (TEA) é um distúrbio de neurodesenvolvimento que pode comprometer, em algum grau, a comunicação, socialização e apresentar comportamentos estereotipados e restritos. O objetivo deste artigo foi apresentar resultados dos testes do aplicativo ACA (Aprendendo com Comunicação Alternativa), que utiliza imagens de Atividades de Vida Diária para ensinar a nomeação de objetos, alfabeto, sílabas e palavras, e verificar se ocorreu ganho de vocabulário e auxílio à alfabetização, como também questões de usabilidade e gamificação. Os testes foram feitos com 28 crianças diagnosticadas com TEA de graus leve e moderado. Os resultados mostraram que tal aplicativo é eficaz no que promete, visto que as crianças ganharam vocabulário. IntroduçãoDe acordo com Ramdoos et al. (2011), o Transtorno do Espectro Autista (TEA) é um distúrbio do desenvolvimento neurológico de início precoce, caracterizado por comprometer a comunicação, habilidades sociais e comportamentos estereotipados ou

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People's usage of social networks, mobile applications, websites, sensor networks and other computer systems leads to a massive production of personal data about their behaviors and preferences. Personal data are used by organizations in business and marketing tasks. However, details about personal data usage are often not accessible or clear to data subject, raising concerns about privacy and security. Presentation of information about personal data usage needs improvement towards Personal Data Transparency. Thus, this paper aims to present the TR-Model, a Metadata Application Profile guideline that intends to propose a standardization on information to be considered minimally necessary to Personal Data Transparency as well as a set of specifications to guide developers on how to present this data. TR-Model elements are focused providing Personal Data Transparency in a user-friendly and high quality format. TR-Model presents a set of specification based on entities, metadata, metaevents and descriptions. The model evaluation was based on user testing in several scenarios of usage of personal data in a gym application tool. The information presented was created based on the TR-Model metadata, metaevents and descriptions. Participants evaluated transparency considering dimensions of Human-Computer Interaction and Information Quality. Participants' opinions were recorded in surveys and analyzed with descriptive statistics; the results indicate that the TR-Model was effective in supporting the production of friendly, understandable and relevant Transparency for data subjects, in compliance with regulations like GDPR.

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