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Enregistrement W2129912275 · doi:10.1002/14651858.cd009115.pub2

Phonics training for English-speaking poor readers

2012· review· en· W2129912275 sur OpenAlexaboutno aff
Genevieve McArthur, Philippa Eve, Kristy Jones, Erin Banales, Saskia Kohnen, Thushara Anandakumar, Linda Larsen, Eva Marinus, Hua‐Chen Wang, Anne Castles

Notice bibliographique

RevueCochrane Database of Systematic Reviews · 2012
Typereview
Langueen
DomainePsychology
ThématiqueReading and Literacy Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPhonicsPsycINFOCitationReading (process)LiteracyCINAHLMedical educationPsychologyMEDLINEMedicinePsychological interventionMathematics educationLibrary scienceComputer sciencePedagogyLinguisticsNursingPrimary educationPolitical science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Around 5% of English speakers have a significant problem with learning to read words. Poor word readers are often trained to use letter-sound rules to improve their reading skills. This training is commonly called phonics. Well over 100 studies have administered some form of phonics training to poor word readers. However, there are surprisingly few systematic reviews or meta-analyses of these studies. The most well-known review was done by the National Reading Panel (Ehri 2001) 12 years ago and needs updating. The most recent review (Suggate 2010) focused solely on children and did not include unpublished studies. OBJECTIVES: The primary aim of this review was to measure the effect that phonics training has on the literacy skills of English-speaking children, adolescents, and adults whose reading was at least one standard deviation (SD), one year, or one grade below the expected level, despite no reported problems that could explain their impaired ability to learn to read. A secondary objective was to explore the impact of various factors, such as length of training or training group size, that might moderate the effect of phonics training on poor word reading skills. SEARCH METHODS: We searched the following databases in July 2012: CENTRAL 2012 (Issue 6), MEDLINE 1948 to June week 3 2012, EMBASE 1980 to 2012 week 26, DARE 2013 (Issue 6), ERIC (1966 to current), PsycINFO (1806 to current), CINAHL (1938 to current), Science Citation Index (1970 to 29 June 2012), Social Science Citation Index (1970 to 29 June 2012), Conference Proceedings Citation Index - Science (1990 to 29 June 2012), Conference Proceedings Citation Index - Social Science & Humanities (1990 to 29 June 2012), ZETOC, Index to Theses-UK and Ireland, ClinicalTrials.gov, ICTRP, the metaRegister of Controlled Trials, ProQuest Dissertations and Theses, DART Europe E-theses Portal, Australasian Digital Theses Program, Education Research Theses, Electronic Theses Online System, Networked Digital Library of Theses and Dissertations. Theses Canada portal, www.dissertation.com, and www.thesisabstracts.com. We also contacted experts and examined the reference lists of published studies. SELECTION CRITERIA: We included studies that use randomisation, quasi-randomisation, or minimisation to allocate participants to either a phonics intervention group (phonics alone, phonics and phoneme awareness training, or phonics and irregular word reading training) or a control group (no training or alternative training, such as maths). Participants were English-speaking children, adolescents, or adults whose word reading was below the level expected for their age for no known reason (that is, they had adequate attention and no known physical, neurological, or psychological problems). DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies, assessed risk of bias, and extracted data. MAIN RESULTS: We found 11 studies that met the criteria for this review. They involved 736 participants. We measured the effect of phonics training on eight outcomes. The amount of evidence for each outcome varied considerably, ranging from 10 studies for word reading accuracy to one study for nonword reading fluency. The effect sizes for the outcomes were: word reading accuracy standardised mean difference (SMD) 0.47 (95% confidence interval (CI) 0.06 to 0.88; 10 studies), nonword reading accuracy SMD 0.76 (95% CI 0.25 to 1.27; eight studies), word reading fluency SMD -0.51 (95% CI -1.14 to 0.13; two studies), reading comprehension SMD 0.14 (95% CI -0.46 to 0.74; three studies), spelling SMD 0.36 (95% CI -0.27 to 1.00; two studies), letter-sound knowledge SMD 0.35 (95% CI 0.04 to 0.65; three studies), and phonological output SMD 0.38 (95% -0.04 to 0.80; four studies). There was one result in a negative direction for nonword reading fluency SMD 0.38 (95% CI -0.55 to 1.32; one study), though this was not statistically significant.We did five subgroup analyses on two outcomes that had sufficient data (word reading accuracy and nonword reading accuracy). The efficacy of phonics training was not moderated significantly by training type (phonics alone versus phonics and phoneme awareness versus phonics and irregular word training), training intensity (less than two hours per week versus at least two hours per week), training duration (less than three months versus at least three months), training group size (one-on-one versus small group training), or training administrator (human administration versus computer administration). AUTHORS' CONCLUSIONS: Phonics training appears to be effective for improving some reading skills. Specifically, statistically significant effects were found for nonword reading accuracy (large effect), word reading accuracy (moderate effect), and letter-sound knowledge (small-to-moderate effect). For several other outcomes, there were small or moderate effect sizes that did not reach statistical significance but may be meaningful: word reading fluency, spelling, phonological output, and reading comprehension. The effect for nonword reading fluency, which was measured in only one study, was in a negative direction, but this was not statistically significant.Future studies of phonics training need to improve the reporting of procedures used for random sequence generation, allocation concealment, and blinding of participants, personnel, and outcome assessment.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,518
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0110,004
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0110,002
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,278
Tête enseignante GPT0,435
Écart entre enseignants0,156 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations157
Publié2012
Routes d'admission1
Résumé présentoui

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