Towards Language Independent Detection of Dyslexia with a Web-based Game

Rauschenberger, Maria; Rello, Luz; Baeza-Yates, Ricardo; Bigham, Jeffrey P.

doi:10.1145/3192714.3192816

Cited by 26 publications

(21 citation statements)

References 30 publications

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“…Medical Therapy [1, 26-29, 45, 46, 58, 67, 81, 87, 95, 121, 125, 129, 130] Diagnosis [7,34,57,78,95,101,102,110,115,134] Training [54-56, 91, 103, 132, 138] Social Collaboration [8,9,13,16,17,49,83,94,96,98,105,122] Education [12,18,25,36,48,59,60,65,69,82,86] Communication [14,45] Sports [36,52] Work Skills [75,128] Art & Public [34,53] Identity Free Play [77,104,[106][107][108]137] Table 7. Purpose categorisation w...…”

Section: Modelmentioning

confidence: 99%

The Purpose of Play

Spiel

Gerling

2021

ACM Trans. Comput.-Hum. Interact.

118

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Play presents a popular pastime for all humans, though not all humans play alike. Subsequently, Human–Computer Interaction Games research is increasingly concerned with the development of games that serve neurodivergent 1 players. In a critical review of 66 publications informed by Disability Studies and Self-Determination Theory, we analyse which populations , research methods, kinds of play and overall purpose goals existing games address. We find that games are largely developed for children, in a top-down approach. They tend to focus on educational and medical settings and are driven by factors extrinsic to neurodivergent interests. Existing work predominantly follows a medical model of disability, which fails to support self-determination of neurodivergent players and marginalises their opportunities for immersion. Our contribution comprises a large-scale investigation into a budding area of research gaining traction with the intent to capture a status quo and identify opportunities for future work attending to differences without articulating them as deficit.

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Section: Modelmentioning

confidence: 99%

The Purpose of Play

Spiel

Gerling

2021

ACM Trans. Comput.-Hum. Interact.

118

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“…Gaggi et al [6] in their work uses six various auditory and visual games with 24 participants of the kinder garden to discover the dyslexia children and train different skills hidden inside them. This game model not only predicts the possibility of dyslexia at the same time it also discovers unique skill among those children's and tune them accordingly.Maria Rauschenberger et al [7] exposed in their work about eight game measures for detecting dyslexia among Spanish children's. It is a web application for the easy screening process and suggests them the assistance they need.…”

Section: Related Workmentioning

confidence: 99%

Whale Behavior based Rule Optimization on Paraconsistent Neutrosophic Classification Model for Prediction of Dyslexia

Zeema¹,

Christopher²

2019

IJRTE

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With the advancement in the software field, diagnosing dyslexia in earlier stages among children is highly possible. It helps them to take necessary measures to rise above the problem. This paper intends to develop an uncertainty handling model using neutrosophic logic inference system. This system’s functionality is enhanced by introducing paraconsistent logic with whale behavior based optimization. Paraconsistent logic is used to discover the degree of certainty and contradiction of generated rules. Pruning the population of rules is handled by a nature inspire algorithm known as whale behavior based rule optimization. Dyslexia dataset consists of both vague and crisp values. Treating them as such will often lead to high false alarms in the detection process. To overcome this issue the neutrosophic model is used to denote them in terms of membership degree of truthiness, indeterminacy, and falsity. The paraconsistent analyzer works with the favorable and unfavorable degree of evidence of each rule to handle the inconsistency and uncertainty among dyslexia detection. The potential rules are selected by the encircle prey model of the whale optimization algorithm. The simulation results proved that the performance of the proposed model produces high detection rate in the detection of dyslexia.

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“…There are three other on-going projects for early risk detection of dyslexia that have not yet reported significant results yet: one approach for Italian tested with 24 pre-schoolers [9], and a languageindependent approach MusVis evaluated with German, English and Spanish children [19,24].…”

Section: Computer Based Gamesmentioning

confidence: 99%

“…(i) linguistic analyses of 833 confusion sets 3 , created from the errors of people with dyslexia writing in English [18]; and (ii) Performance measures from the linguistic exercises of an online game called Piruletras. 4 This game is part of previous work targeting children with dyslexia to improve spelling performance [24]. We selected exercises that were more challenging for the players (those with higher error rates and need for more time to be solved) since those exercises were more likely to manifest dyslexia difficulties.…”

Section: Content Designmentioning

confidence: 99%

Screening Dyslexia for English Using HCI Measures and Machine Learning

Rello

Romero

Rauschenberger

et al. 2018

Proceedings of the 2018 International Conference on Digital Health

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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.

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Towards Language Independent Detection of Dyslexia with a Web-based Game

Cited by 26 publications

References 30 publications

The Purpose of Play

The Purpose of Play

Whale Behavior based Rule Optimization on Paraconsistent Neutrosophic Classification Model for Prediction of Dyslexia

Screening Dyslexia for English Using HCI Measures and Machine Learning

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