<i>“It’s never too late</i> ”: Adult students and music learning in one online and offline convergent community music school
Bibliographic record
Abstract
This study is the third and final part of a longitudinal ethnographic investigation of music learning and teaching of the Online Academy of Irish Music (OAIM), an Irish music “school” situated in both online ( www.oaim.ie ) and offline (Doolin, County Clare, Ireland) contexts. We first examined the online OAIM through teacher narratives in 2011. In the second part of the study, we explored the OAIM through students’ perspectives at the OAIM’s first offline Irish flute summer school retreat week in July 2013. In this third part and final part of the study, we attended the OAIM’s offline tin whistle school week in October 2015 in Ennis, Ireland. The purpose of this part of the study was to continue our investigation of adult music learners who learned Celtic music through the OAIM, as it has continued to evolve as an online and offline convergent community music school. Findings indicate that the adult participants benefited from learning music through a combination of aural/oral, observational, and written notation in both online and offline contexts, but had differing perspectives as to what worked for them and what did not. As an online and offline convergent school, the OAIM offers an intriguing model of music learning and teaching for school music contexts and community music schools.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".