A population-level analysis of associations between school music participation and academic achievement.
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.
Notice bibliographique
Résumé
[Correction Notice: An Erratum for this article was reported online in Journal of Educational Psychology on Oct 17 2019 (see record 2019-62704-001). In the original article, Tables 2 and 4 contained typographical errors regarding the reporting of some sample sizes. In Table 2, for the Unadjusted Analyses section, the n for the “No participation in school music” group should read 75,616 for the Math 10 group, and 95,873 for the Science 10 group while the n for the “Participation in school music” group should read 13,772 for the Math 10 group, and 15,416 for the Science 10 group. In Table 4, for the Unadjusted Analyses section, the n for the “No participation in school music” group should read 75,616 for the Math 10 group, and 95,873 for the Science 10 group. All calculations were based on the correct sample sizes, the typographical error was isolated to n reported in the aforementioned instances in these two tables. All versions of this article have been corrected.] The present study employed population-level educational records from 4 public school student cohorts (n = 112,916; Grades 7–12) in British Columbia (Canada) to examine relationships between music education (any participation, type of participation, music achievement, and engagement level) and mathematics and science achievement in Grade 10 as well as English achievement in Grades 10 and 12, while controlling for language/cultural background, Grade 7 academic achievement, and neighborhood socioeconomic status. Music participation was related to higher scores on all 4 subjects and these relationships were stronger for instrumental music than vocal music (Cohen’s d range: .28 to .44 [small-medium effect sizes] and .05 to .13 [null-small effect sizes]). School music achievement positively related to scores on all subjects; such relationships were stronger for achievement in instrumental music compared with vocal music. Higher levels of music engagement (number of courses) was related to higher exam scores on all subjects; this pattern was more pronounced for very high engagement in instrumental music (d range: .37 to .55; medium effect sizes) compared with vocal music (d range: .11 to .26; small effect sizes). The effect sizes of these group differences are greater than the effect sizes corresponding to average annual gains of students’ academic achievement during high school—in other words, highly engaged instrumental music students were, on average, academically over 1 year ahead of their peers. The findings suggest that multiyear engagement in music, especially instrumental music, may benefit high school academic achievement. Findings and implications are discussed within the broader interdisciplinary literature on music learning. (PsycINFO Database Record (c) 2020 APA, all rights reserved)
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,000 |
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.
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 découle