MétaCan
Menu
Retour à la cohorte
Enregistrement W1997475288 · doi:10.1037/0022-0663.94.2.278

Relationships between instructional language and primary students' learning.

2002· article· en· W1997475288 sur OpenAlexaff
Judith C. Lapadat

Notice bibliographique

RevueJournal of Educational Psychology · 2002
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueEFL/ESL Teaching and Learning
Établissements canadiensUniversity of Northern British Columbia
Organismes subventionnairesnon disponible
Mots-clésPsychologyMathematics educationPrimary educationLanguage acquisitionPedagogyCognitive psychology

Résumé

récupéré en direct d'OpenAlex

Causal modeling was used to examine how primary students’ language ability interacted with pace and redundancy of instructional language during an expository science lesson to explain students’ attention and learning. Language ability and pace of the instructional language, mediated by students’ attention to the lesson, accounted for significant variance in learning outcomes. Higher language ability related to greater learning. Overall, slow-paced instructional language was positively related to learning, but students attended less to it than to fast-paced talk. Students with special needs attended significantly less and learned less, whereas students not so identified attended slightly less but learned more. Teachers’ talk matters, but because instructional language impacts differentially on students, heuristics for modifying it are not straightforward. In communicative settings involving large groups, most individuals do more listening than talking. This is particularly so for students in many elementary classrooms, where the teacher does up to 80% of the talking, and the remaining 20% of the talking time is shared by all of the students (Cazden, 1988). Despite recent changes in educational practices (Lapadat 2000a, 2000b; Pappas, Kiefer, & Levstik, 1999), this nonreciprocity of talking time persists across educational levels. In such classrooms, students’ receptive language knowledge and the listening strategies they use have a close relationship with their academic learning outcomes. However, even in classrooms where talk is distributed more equitably than in typical whole-class expository teaching, such as in constructivist, small group, and cooperative learning models (Lauritzen & Jaeger, 1997), students’ ability to engage, listen, and respond are still important determinants of both communicative and academic success. Roth and Spekman (1989) called for more research focusing on students’ knowledge of and ability to understand and use language, pointing out that this is crucial in coming to understand how students understand, participate in, and learn from the interactions that make up instruction. Even during expository instruction, talk is constructed interactively (O’Connor & Michaels, 1996; Pappas et al., 1999). Just as young primary school students have the task of attending to and understanding the teacher’s talk (and peers’ talk) in order to learn in school, so too does the teacher need to talk in ways that students understand in order to teach effectively (Derwing, 1991). If students have insufficient linguistic knowledge or do not engage, or if teachers fail to adjust their instructional language, academic learning will be affected. As expository instruction is so frequently used in schools, it is all the more important to do it well. In classrooms in which talk is distributed differently than in wholeclass expository teaching, teachers’ effective use of instructional language in small groups or with individuals, as well as in segments of whole-class instruction, remains a critical component of effective teaching (Lindsay, 1996; Merritt, 1982; O’Connor & Michaels, 1996). This is a challenging task, as students bring diverse understandings to learning, based on their prior knowledge, language skills, cognitive processing abilities, cultural perspectives, motivations, and interests.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge 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 enseignants0,226
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,075
Tête enseignante GPT0,348
Écart entre enseignants0,273 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations4
Publié2002
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJournal of Educational PsychologyMême sujetEFL/ESL Teaching and LearningTravaux en français237 207