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Predicting risk of dyslexia with an online gamified test.
Rello, Luz; Baeza-Yates, Ricardo; Ali, Abdullah; Bigham, Jeffrey P; Serra, Miquel.
Afiliação
  • Rello L; Department of Information Systems and Technology, IE Business School, IE University, Madrid, Spain.
  • Baeza-Yates R; Khoury College of Computer Sciences, Northeastern University at Silicon Valley, San Jose, CA, United States of America.
  • Ali A; School of Computer Science, University of Washington, Seattle, WA, United States of America.
  • Bigham JP; Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, United States of America.
  • Serra M; Department of Cognition and Development, University of Barcelona, Barcelona, Spain.
PLoS One ; 15(12): e0241687, 2020.
Article em En | MEDLINE | ID: mdl-33264301
ABSTRACT
Dyslexia is a specific learning disorder related to school failure. Detection is both crucial and challenging, especially in languages with transparent orthographies, such as Spanish. To make detecting dyslexia easier, we designed an online gamified test and a predictive machine learning model. In a study with more than 3,600 participants, our model correctly detected over 80% of the participants with dyslexia. To check the robustness of the method we tested our method using a new data set with over 1,300 participants with age customized tests in a different environment -a tablet instead of a desktop computer- reaching a recall of over 78% for the class with dyslexia for children 12 years old or older. Our work shows that dyslexia can be screened using a machine learning approach. An online screening tool in Spanish based on our methods has already been used by more than 200,000 people.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atenção / Dislexia / Aprendizado de Máquina / Testes Neuropsicológicos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Atenção / Dislexia / Aprendizado de Máquina / Testes Neuropsicológicos Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Espanha