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Record W2287511650 · doi:10.1145/2839462.2854104

Exploring the Design Space of Tangible Systems Supported for Early Reading Acquisition in Children with Dyslexia

2016· article· en· W2287511650 on OpenAlexaff
Min Fan, Alissa N. Antle, Emily S. Cramer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDyslexiaReading (process)Context (archaeology)Space (punctuation)Learning to readComputer scienceCognitive psychologyHuman–computer interactionPsychologyMultimediaLinguistics

Abstract

fetched live from OpenAlex

Tangible user interfaces have the potential to support children in learning to read. This research explores the design space of school-based tangible learning systems that support early reading acquisition in children, particularly in children with reading difficulties. Informed by theories of the causes and interventions for dyslexia and research on TUIs for learning, we present the design of a tangible reading system that uses the dynamic colour and tactile cues to help children with dyslexia to learn English letter-sound correspondences. We then propose a case study design that investigates how this system can support children with dyslexia aged 7-8 years old in learning letter-sound correspondences in a school context. We conclude by discussing the future work and potential contributions of this research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.267
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

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