Visualizing art education in the twenty-first century: Mapping the themes of art educators through the NAEA convention, c. 2000–2015
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This article presents a visual analysis of the National Art Education Association annual conference programmes from 2000 to 2015 to provide an understanding of the themes and topics that practitioners in the field of art education have presented in the twenty-first century. Over this period, themes such as curriculum, learning and teaching were consistently represented, while themes such as aesthetics were less used and themes such as visual culture emerged. Given the advancement of digital data visualization methods, we revisit the convention catalogue as a rich source of archival material to identify the thematic patterns and diversity in our field. Data visualizations can assist in making visible certain patterns and trends that can confirm, run counter, or diverge from our individual perception of an event. In this article, we identify some of the persistent, fading and emergent themes pursued by art education practitioners. We conclude by examining the theme elements and principles, which have considerable importance in the recent literature on art education, yet are curiously absent from the themes in convention presentations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it