Instrumental Technique, Expressivity, and Communication. A Qualitative Study on Learning Music in Individual and Collective Settings
Bibliographic record
Abstract
In this paper, we present a qualitative study comparing individual and collective music pedagogies from the point of view of the learner. In doing so, we discuss how the theoretical tools of embodied cognitive science (ECS) can provide adequate resources to capture the main properties of both contexts. We begin by outlining the core principles of ECS, describing how it emerged in response to the information-processing approach to mind, which dominated the cognitive sciences for the latter half of the 20th century. We then consider the orientation offered by ECS and its relevance for music education. We do this by identifying overlapping principles between three tenets of ECS, and three aspects of pedagogical practice. This results in the categories of "instrumental technique," "expressivity," and "communication," which we adopted to examine and categorize the data emerging from our study. In conclusion, we consider the results of our study in light of ECS, discussing what implications can emerge for concrete pedagogical practices in both individual and collective settings.
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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 | 0.017 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".