Bibliographic record
Abstract
In this article, we describe the effects on student achievement and attitudes of a Canadian school-wide, arts education approach, Learning Through the Arts ( LTTA ). Our sample included over 6000 students and their parents, teachers, and principals. We gathered data, both at the outset and after three years of involvement in LTTA on student achievement, student attitudes towards arts and schooling, and out-of-school activities. We found no baseline differences in achievement nor in socioeconomic status in the LTTA and control schools. At the end of three years, the grade-6 LTTA students scored significantly higher on tests of computation than students in control schools. We conclude the article with suggestions for extending this longitudinal research. Keywords: arts-based learning, arts-based schooling, engagement, arts and achievement Dans cet article, les auteures decrivent les effets sur le rendement scolaire et les attitudes des eleves du programme Apprendre par les arts (APLA) implante dans un reseau scolaire. Lechantillon regroupait plus de 6000 eleves, les parents, les enseignants et les directeurs des ecoles canadiennes participantes. Les auteurs ont collige, au debut dimplantation du programme APLA et apres une periode de trois ans dapplication, des donnees sur le rendement des eleves, leurs attitudes envers les arts et lecole et les activites extrascolaires. Il ny avait aucune difference de base quant au rendement ou au statut socioeconomique entre les ecoles ayant recours au programme APLA et les ecoles temoins. Au terme de letude de trois ans, les eleves qui ont appris avec le programme APLA ont obtenu en mathematiques des notes nettement superieures a celles des eleves des ecoles temoins. Mots cles: enseignement et apprentissage par les arts, participation, arts et rendement des eleves.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".