Teaching and Learning Popular Music in Higher Education Through Interdisciplinary Collaboration: Practice What You Preach
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
This article provides a contextualized explanation of an emerging strategy for popular music teaching and learning in higher education that the authors term Improvisatory Integrative Learning. This strategy coalesces around four themes from a Do-It-Yourself and Do-It-With-Others ethos: autonomy, play, peer learning, and peer teaching. To explicate the possibilities and pitfalls of teaching popular music in this way, the authors analyze the approaches taken in a co-taught university course integrating two perspectives: music education and ethnomusicology. The interdisciplinary collaboration became an investigative space for informal music learning approaches in a formal context, in which students improvised with creative composition. We explore not only how processes that are part and parcel of popular music learning can help improve productivity in a popular music classroom, but also the ways that improvisatory integrative learning can serve a diverse university student population by expanding interdisciplinary approaches to multiple kinds of subject matter.
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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 | 0.000 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it