Predicting risk of dyslexia with an online gamified test
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 st...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | IE |
| Repositorio: | Repositorio IE |
| OAI Identifier: | oai:repositorio.ie.edu:20.500.14417/3068 |
| Acceso en línea: | https://doi.org/10.1371/journal.pone.0241687 https://hdl.handle.net/20.500.14417/3068 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097123728&doi=10.1371%2fjournal.pone.0241687&partnerID=40&md5=af988696d1805c4b5ee8f31e2530d3b9 |
| Access Level: | acceso abierto |
| Palabra clave: | adolescent child controlled clinical trial controlled study dyslexia female human machine learning major clinical study male mass screening online system prediction risk assessment risk factor attention language neuropsychological test pathophysiology phonetics physiology reading semantics short term memory video game vision Adolescent Attention Child Dyslexia Female Humans Language Machine Learning Male Memory Short-Term Neuropsychological Tests Phonetics Reading Risk Factors Semantics Video Games Vision Ocular 58 Pedagogía::5801 Teoría y métodos educativos::5801.05 Pedagogía experimental ODS 4 - Educación de calidad |
| Sumario: | 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. © 2020 Rello et al. This is an open access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original author and source are credited. |
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