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Enregistrement W2026357981 · doi:10.1037/0708-5591.49.2.118

A statistical learning perspective on children's learning about graphotactic and morphological regularities in spelling.

2008· article· en· W2026357981 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

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Notice bibliographique

RevueCanadian Psychology/Psychologie canadienne · 2008
Typearticle
Langueen
DomainePsychology
ThématiqueReading and Literacy Development
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésSpellingPsychologyPerspective (graphical)LinguisticsCognitive scienceCognitive psychologyArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

We put forward our view on how children learn to spell through a review of recent research on English and French children's spelling development. We examine children's learning of graphotactic conventions (legal combinations of letters), followed by a more in-depth treatment of how children learn the place of morphemes (smallest units of meaning in language) in spelling. We contrast findings from recent research with those of traditional models that suggest that children use both graphotactic and morphological information relatively late in their spelling careers and that the end-point of development, particularly for morphological conventions, lies in rule-based performance. Instead, it seems that quite young children's spellings are influenced by both graphotactic and morphological patterns and that writers do not rely (at least exclusively) on rules. We consider the possibility that children might use statistical learning to gain knowledge of both graphotactic and morphological features of the orthography. Keywords: morphology, spelling acquisition, orthographic learning, spelling development The English and French orthographies adhere to several types of regularities: specifically, phonological, graphotactic, and morphological. In this article, we put forward our view on how children's spellings are influenced by these consistencies, with a special focus on learning of graphotactic and morphological regularities. Our approach draws on the statistical learning perspective, in which it is important to consider the regularities in the (written) input on which children could rely. Accordingly, we begin by considering the kind of information represented in the English and French orthographies. French and English, like most alphabetic orthographies, rely in part on the regular connections between letters and sounds to generate word spellings. This is the case for the words cat and non (no). And yet this phonological basis does not explain the variability with which sounds are represented across different words. For example, the /eI/ sound can be spelled with -ay, -ey, -eigh, -a, and -ea at the ends of words in English and with -ez, -ai, -e, -ef, -ee, and -aie at the end of words in French. A second source of information useful to spelling comes from graphotactic regularities about the legal combinations of letters.' In French, words cannot end in a consonant doublet on its own (e.g., pomme, but not *pomm_ for the word apple in French), but they can in English. In English it is extremely unusual for words to start with consonant doublets (e.g., full, but not *fful), and such patterns never occur in French. These graphotactic patterns determine, in part, the specific letters that make up the spellings of words in both English and French. A third level of consistency in spelling comes from the smallest units of meaning in language, or morphemes. The use of morphological information determines the choice between several plausible representations of a given sound. The decision between the many different spellings of/e/ (as in bed, head, and said) is simple for some words when morphology is considered (e.g., ea in health driven by the root heal). Similarly, the sound /et/ has many different spellings in French (e.g., -aite, -ete or -ete), but a word ending in a diminutive suffix is always spelled -ette (as in fillette, little girl). Morphology even sometimes overrides the phonological basis of spelling. English regular past tense verbs end in the letters -ed, despite the pronunciation of these letters as either /t/, /d/ or /Id/ (as in walked, warned, and spotted). Similarly, in French the letters -ai are used for the sound 3 in faiseur (/fazr/, producer) to preserve the spelling of the root (faire /fer/, to do), despite the fact that e is the typical spelling of this sound. In the above examples, morphology could be useful, but success in spelling could also be achieved through word-specific memorization. …

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.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,136
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,026
Tête enseignante GPT0,305
Écart entre enseignants0,278 · 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