The Artistry of Innovation: Increasing Teachers' Artistic Quotient for Innovative Efficacy.
Bibliographic record
Abstract
This article presents a new model of building capacity for innovative teaching that I call Artistic Quotient (AQ). The purpose of the study was to test the model with generalist teachers who were registered in a professional learning program for innovative teaching through the arts. The procedure employed a one-way, within-subjects, quasi-experimental design using psychometric scales to measure program effects through pre- and post-surveys. Results include a statistically significant increase in teachers’ creative and aesthetic capabilities and innovative teacher efficacy, with the conclusion that increasing teacher AQ increases innovative teacher efficacy. Implications for teacher preparation, professional learning, and innovation education are discussed. Keywords: Artistic Teacher; Artistic Quotient (AQ); Teacher Innovation; Arts Integration; Creative Practice; Design Thinking; Aesthetic Awareness; Innovative Teacher Efficacy; Artistic Capabilities; Social Learning Theory
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How this classification was reachedexpand
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".