Research on the development of academic skills: Introduction to the special issue on early literacy and early numeracy.
Notice bibliographique
Résumé
Welcome to the special issue on early literacy and early numeracy. We have a diverse collection of articles, elicited by asking researchers to submit short succinct manuscripts describing their recent research in one of these areas. The breadth of submissions received was surprising. The term early elicited manuscripts involving children as young as three and as old as ten, and the topics ranged from the relation between home literacy activities and reading acquisition to children's ability to estimate the sums of three-digit numbers. Despite the breadth of topics, however, there are several themes that tie these papers together. The first theme is that novice readers or calculators often use surprisingly sophisticated conceptual knowledge in their cognitive activities. In the present issue, Klein and Bisanz outline the role of early conceptual abilities in the addition performance of 4-year-olds. Senechal shows that 7-year-olds make use of morphological information to spell words. Bialystok and Codd explore the abilities of 3- to 7-year-olds in representing quantities. Lemaire, Lecacheur, and Farioli examine how 10-year-olds use sophisticated strategies to solve estimation problems. Across the seven papers in this issue, children showed an impressive variety of conceptual abilities, as well as some interesting limitations. A second theme that arises from several papers in this issue is the important role for experiential factors in cognitive development. Evans, Shaw, and Bell describe the relations between parent teaching activities and reading acquisition. Miller, Major, Shu, and Zhang show how language influences children's emerging numerical competencies. Such research suggests that closer attention to the wider community of learning that children experience will provide important insights into patterns of cognitive development. A third theme that arose serendipitously from our selection of researchers was that four of the seven papers in this special issue include or are based solely on the performance of children who speak a language other than English (i.e., Lemaire et al.; Miller et al.; Senechal; SprengerCharolles, Cole, Lacert, & Serniclaes). Research on cognitive development should be greatly enhanced by looking beyond an Anglo-centric perspective. A fourth theme of these papers, diversity in methodology, may represent somewhat of a departure from a typical collection of papers in the Canadian Journal of Experimental Psychology. The papers in this special issue represent a wide diversity of methods, running the gamut from correlational designs (Evans et al.) and reading-level and age-level matching designs (Sprenger-Charolles et al.) to methods that more closely resemble traditional experimental paradigms (e.g., Klein & Bisanz; Lemaire et al.; Senechal). We feel that all of these methods have a place in a broad understanding of cognitive development. Three- and four-year-olds are seldom amenable to the multi-trial, data-intensive approach that characterizes research on adult cognitive processes. Often, research on cognitive processes in children begins with observational studies, and progresses (slowly!) to focused experimental work. Children lead busy lives, and as researchers, we are limited in the amount of behaviour that we are able to extract from them. It should be clear from this set of papers that a diversity of methods does not mean a lowering of the standards for scientific research. Furthermore, each paper in this special issue presents a unique perspective, topic, or methodology, adding to the array of tools that can be accessed to advance research in this area. In the next two sections, I will briefly discuss how each of the papers contributes to the accumulation of knowledge in the areas of either early literacy or early numeracy. DEVELOPMENT OF EARLY LITERACY Three of the papers in this issue address questions in the area of early literacy (Evans et al. …
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,006 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,006 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,015 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».