Mapping Research With a Systematic Review: The Example of Social and Emotional Learning in Art Education
Bibliographic record
Abstract
Social and emotional learning (SEL) standards and policies are quickly being adopted across the United States. States and school districts are now requiring demonstrations of SEL in schools and hoping for evidence that school subjects, including art education, can successfully meet those requirements and provide that evidence. This article reports the results of a review of research on the relationship between art education and SEL for three purposes: (1) to illustrate the process of a systematic review of research in a small field, (2) to propose a foundation on which researchers can build, and (3) to map empirical research results about preK–12 SEL in art education for instructional practice. The article contributes to research by offering an instrument to aid systematic reviews in the field. It also summarizes the conclusions of the found empirical research articles on SEL in preK–12 art education contexts.
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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 | 0.209 | 0.497 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.047 | 0.061 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".