Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

Banner header
61.603 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Departaments
  • Departament de Ciències de la Computació
  • Ponències/Comunicacions de congressos
  • View Item
  •   DSpace Home
  • E-prints
  • Departaments
  • Departament de Ciències de la Computació
  • Ponències/Comunicacions de congressos
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Screening dyslexia for English using HCI measures and machine learning

Thumbnail
View/Open
DigitalHealth2018.pdf (566,8Kb)
 
10.1145/3194658.3194675
 
  View Usage Statistics
  LA Referencia / Recolecta stats
Cita com:
hdl:2117/123915

Show full item record
Rello, Luz
Romero Merino, EnriqueMés informacióMés informacióMés informació
Rauschenberger, Maria
Ali, Abdullah
Williams, Kristin
Bigham, Jeffrey P.
White, Nancy Cushen
Document typeConference report
Defense date2018
PublisherAssociation for Computing Machinery (ACM)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
Abstract
More than 10% of the population has dyslexia, and most are diagnosed only after they fail in school. This work seeks to change this through early detection via machine learning models that predict dyslexia by observing how people interact with a linguistic computer-based game. We designed items of the game taking into account (i) the empirical linguistic analysis of the errors that people with dyslexia make, and (ii) specific cognitive skills related to dyslexia: Language Skills, Working Memory, Executive Functions, and Perceptual Processes. . Using measures derived from the game, we conducted an experiment with 267 children and adults in order to train a statistical model that predicts readers with and without dyslexia using measures derived from the game. The model was trained and evaluated in a 10-fold cross experiment, reaching 84.62% accuracy using the most informative features.
CitationRello, L., Romero, E., Rauschenberger, M., Ali, A., Williams, K., Bigham, J., White, N. Screening dyslexia for English using HCI measures and machine learning. A: International Conference on Digital Health. "Proceedings of the 2018 International Conference on Digital Health, DH 2018: Lyon, France, April 23-26, 2018". New York: Association for Computing Machinery (ACM), 2018, p. 80-84. 
URIhttp://hdl.handle.net/2117/123915
DOI10.1145/3194658.3194675
ISBN978-1-4503-6493-5
Publisher versionhttps://dl.acm.org/citation.cfm?id=3194675
Collections
  • Departament de Ciències de la Computació - Ponències/Comunicacions de congressos [1.249]
  View Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
DigitalHealth2018.pdf566,8KbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Contact Us
  • Send Feedback
  • Privacy Settings
  • Inici de la pàgina