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Instructional Methods that Foster the Reading Development of Students with Significant Intellectual Disabilities

2015· article· en· W1969604586 on OpenAlexvenueno aff
Colleen Wood-Fields, Sharon Judge, Silvana M. R. Watson

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2015
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsFluencyPhonicsReading (process)Phonemic awarenessPsychologyVocabularyReading comprehensionMathematics educationSpecial educationPedagogyLiteracyPrimary educationLinguistics

Abstract

fetched live from OpenAlex

Educational legislation has made reading a priority for students with significant intellectual disabilities (ID) and associated speech, language, sensory, or physical impairments. Historically, reading instruction for students with significant ID has focused on sight word instruction, with limited exposure to other essential reading skills. This article focuses on the evidence-based instructional methods that effectively and efficiently foster the reading development of students with significant ID. The authors reviewed the literature from the past 20 years on reading interventions for students with significant ID. In spite of access and opportunity barriers that have inhibited the reading development of students with significant ID, a synthesis of the empirical research on reading instruction suggests that students with significant ID and associated disabilities can learn phonemic awareness, phonics, vocabulary, fluency, and comprehension skills with direct instruction. Implications for providing reading instruction that effectively promotes reading development are discussed and areas for future research are identified.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.140
GPT teacher head0.398
Teacher spread0.259 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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