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Record W4200059063 · doi:10.53967/cje-rce.v44i4.4723

Impact of Multi-Sensory Phonics Programs in Teaching English as an Additional Language

2021· article· en· W4200059063 on OpenAlexaffvenueabout
James Ludvig Langille, Zoila Green

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2021
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPhonicsEllReading (process)Whole languageMathematics educationComputer sciencePedagogyPsychologyTeaching methodLinguisticsPrimary educationVocabulary development

Abstract

fetched live from OpenAlex

Complexity of the various needs that come with English language learners (ELLs) beyond language learning (such as learning gaps, social and cultural differences, etc.) and increased numbers of English language learners in Canadian schools have led educational stakeholders to seek ways to promote reading improvement. While literature points out the relevance of systematic phonics instruction in reading and the importance of form-focused instruction (FFI) in English language learning, multi-sensory phonics programs (MSPPs) appear to be an effective reading tool that embodies them both. Although evidence on the efficacy of these programs is copious in students with learning difficulties, little is known about MSPPs in connection with English language learning. As a result, this integrative literature review explores the notable benefits of MSPPs, their connection with ELL instruction, and how successful program implementation may depend on teacher training.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.053
GPT teacher head0.347
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Education / Revue canadienne de l éducation→Same topicReading and Literacy Development→French-language works237,207→