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Predicting risk of dyslexia with an online gamified test

  • Authors
  • Rello L, Baeza-Yates R, Ali A, Bigham JP, Serra M
  • UPF authors
  • RELLO SANCHEZ, MARIA LUZ; BAEZA YATES, RICARDO ALBERTO; SERRA BURRIEL, MIQUEL;
  • Type
  • Articles de recerca
  • Journal títle
  • PLoS ONE
  • Publication year
  • 2020
  • Volume
  • 15
  • Number
  • 12
  • Pages
  • 1-15
  • ISSN
  • 1932-6203
  • Publication State
  • Publicat
  • 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.
  • Complete citation
  • Rello L, Baeza-Yates R, Ali A, Bigham JP, Serra M. Predicting risk of dyslexia with an online gamified test. PLoS ONE 2020; 15(12): 1-15.
Bibliometric indicators
  • 1 times cited Scopus
  • 0 times cited WOS
  • Índex Scimago de 1.023 (2019)