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The study proposes language-independent screening through computer games combined with machine learning. Game content was created, and data were collected from 137 children, including 51 with dyslexia, across German, Spanish, and English. Predictive models using multiple classifiers are evaluated, reporting strong precision and recall and enabling low-cost early online screening using non-linguistic elements.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/screening-dyslexia-using-visual-auditory-computer-games-and-machine-learning/290787/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/screening-dyslexia-using-visual-auditory-computer-games-and-machine-learning/290787.png","ImageObject",300,407,{"name":92,"@type":93},"River Wang","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-18","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main screening approach proposed in this work?","Question",{"text":112,"@type":113},"The work presents a language-independent dyslexia screening approach using computer games and machine learning models trained on game-derived data.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the dataset collected and who participated?",{"text":117,"@type":113},"Data were collected from 137 children playing the designed game, including 51 children with dyslexia, across German, Spanish, and English language contexts.",{"name":119,"@type":110,"acceptedAnswer":120},"Why does the method avoid relying on language-specific dyslexia indicators?",{"text":121,"@type":113},"Instead of using linguistic reading/writing indicators, it focuses on visual and auditory factors that are strongly associated with dyslexia.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},290787,1790021986,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1099514067438,"https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542","IEEE EDUCATION SOCIETY SECTION  \nReceived 26 December 2024, accepted 21 January 2025, date of publication 7 February 2025, date of current version 18 February 2025. Digital Object Identifier 10.1109/ACCESS.2025.3539719  \nScreening Dyslexia Using Visual Auditory Computer Games and Machine Learning  \nMARIA RAUSCHENBERGER 1, RICARDO BAEZA-YATES2,(Fellow, IEEE), AND LUZ RELLO3 1Faculty of Technology, University of Applied Science Emden/Leer, 26723 Emden, Germany  \n2Institute for Experiential AI, Northeastern University at Silicon Valley, San Jose, CA 95113, USA  \n3IE Business School, IE University, 28046 Madrid, Spain Corresponding author: Luz Rello ([luz.rello@ie.edu](luz.rello@ie.edu))  \nThis work was supported in part by the fem:talent Scholarship from the Applied University of Emden/Leer, and in part by the Deutschen Lesepreis 2017 from the Stiftung Lesen and the Commerzbank-Stiftung.  \nThis work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Ministry of Education, Science and Culture of Schleswig-Holstein (Ministeriumfür Bildung, Wissenschaft und Kultur, MBWK) and by the Education Authority of the State of Lower Saxony (Niedersächsische Landesschulbehörde) .  \nABSTRACT Reading acquisition is one the main keys for school success and a crucial component for empowering individuals to participate meaningfully in society. Yet, it is still a challenging skill to acquire for around 10% of children that have dyslexia, a type of neuro-developmental disorder that affects the ability to learn how to read and write. Dyslexia is often under-diagnosed, and normally children with dyslexia are only detected once they fail in school, even though dyslexia is not related to general intelligence. In this work, we present an approach for screening dyslexia using language-independent games in combination with machine learning models. To reach this goal, we designed the content of a computer game, collected data from 137 children playing this game (51 with dyslexia) in different languages-German, Spanish and English-and created a prediction model using different machine learning classifiers. Our method provides a precision of 0.78 and recall of 0.79 for German and a precision of 0.83 and recall of 0.80 for all languages when Extra Trees are used, with an accuracy of 0.67 and 0.75, respectively. Our results open the possibility of inexpensive online early screening of dyslexia for young children using non-linguistic elements.  \nINDEX TERMS Dyslexia, language disorder, language-independence, machine learning, reading disorder, dyslexia screening, serious games.  \nI. INTRODUCTION  \nAchieving reading fluency is considered a critical component for empowering individuals to participate meaningfully in society and is a major contributor to improved livelihoods. However, globally, up to 250 million children are unable to acquire basic literacy skills [1] . While there are many factors which contribute to poor learning outcomes, one widespread challenge is developmental dyslexia, a readingspecific disability, which by some estimates may affect up to 10-15% of the global population [2] . Despite being one of the most common learning disabilities and accounting for up to 80% of diagnosed learning disabilities [3], developmental  \nThe associate editor coordinating the review of this manuscript and  \napproving it for publication was Nkaepe Olaniyi  .  \ndyslexia is still under-diagnosed and often goes untreated, leading in many cases to school failure. In fact, nowadays learning difficulties are the primary cause of eventual school failure and school dropout [4] . For instance, 35% of persons with dyslexia drop out of school, and it is estimated that less than 2% of persons with dyslexia will complete a four-year college degree [5] . Moreover, school failure can lead to an excluded population with limited ability to become productive adults who function independently in soc","cbCaitktug3bTe91","https://ap.wps.com/l/cbCaitktug3bTe91","pdf",2355214,13,"English","# Abstract\n# I. Introduction","[{\"question\":\"What is the main screening approach proposed in this work?\",\"answer\":\"The work presents a language-independent dyslexia screening approach using computer games and machine learning models trained on game-derived data.\"},{\"question\":\"How was the dataset collected and who participated?\",\"answer\":\"Data were collected from 137 children playing the designed game, including 51 children with dyslexia, across German, Spanish, and English language contexts.\"},{\"question\":\"Why does the method avoid relying on language-specific dyslexia indicators?\",\"answer\":\"Instead of using linguistic reading/writing indicators, it focuses on visual and auditory factors that are strongly associated with dyslexia.\"}]","Screening Dyslexia Using Visual Auditory Computer Games and Machine Learning | PDF",1789642567,33]