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Record W1581151324 · doi:10.82308/19809

Attention skills and response to a computer-based literacy intervention

2007· article· en· W1581151324 on OpenAlexafffund
Louise Deault

Bibliographic record

VenueeScholarship@McGill (McGill) · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsMcGill University
FundersConcordia UniversityMcGill University
KeywordsIntervention (counseling)Response to interventionComputer literacyLiteracyComputer sciencePsychologyMathematics educationMedical educationPedagogyMedicine

Abstract

fetched live from OpenAlex

Inattention is often associated with early reading difficulties and to non-responsiveness to reading interventions. The aim of the present study was to explore the relationships between attention skills and literacy skills over the course of the computer-based literacy intervention, ABRACADABRA. The design included a contrast of two interventions, Synthetic Phonics and Rime, against a classroom control, enabling a comparison of different types of literacy contexts for grade one students with varying attention skills. Attention skills, as measured by both parent ratings and a sustained attention task, were found to predict reading-related skills and students' improvement over the course of the intervention. However, the predictive power of attention changed across different literacy contexts. For students who did not participate in the intervention, sustained attention predicted growth in blending skills and inattention predicted reading comprehension improvement, while the Synthetic Phonics group no longer showed these associations. These results suggest that the literacy environment has an impact on the mapping of associations between literacy and attention skills.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.315
Teacher spread0.301 · 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 designOther design
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

Citations2
Published2007
Admission routes2
Has abstractyes

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