Abstract. Talking through mobile apps has become common nowadays and something essential and the WhatsApp is one of this

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

Automatic Short Answer Grading is the study field that addresses the assessment of students' answers to questions in natural language. Besides length, it differs from automatic essay grading by focusing on the evaluation of content instead of answer's style. The grading of the answers is generally seen as a typical classification supervised learning. Many works have been recently developed, but most of them deal with data in the English language. In this paper, we present a new Portuguese dataset and system for automatic short answer grading. The data was collected with the participation of 13 teachers, 12 undergraduate students and 245 elementary school students. Results achieved 69% accuracy in four-class classification and 85% on binary classification.

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