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Record W4411617896 · doi:10.1177/03057356251334568

Inside the piano studio: What teachers say about performance training, perfectionism, and performance anxiety

2025· article· en· W4411617896 on OpenAlexafffundabout
Charlene Ryan, Jessica M. Tsang, Diana Dumlavwalla

Bibliographic record

VenuePsychology of Music · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsOntario Centre of Excellence for Child and Youth Mental HealthToronto Metropolitan University
FundersToronto Metropolitan University
KeywordsPianoPsychologyAnxietyPerfectionism (psychology)StudioTraining (meteorology)Applied psychologyDevelopmental psychologyVisual artsArt

Abstract

fetched live from OpenAlex

Music performance anxiety (MPA) is a common experience among musicians of all ages. However, young pianists have indicated receiving limited performance training or effective MPA support from their teachers. As these findings do not reflect teacher perspectives, this study was designed to provide a fuller picture of piano training. Two hundred thirty-seven piano teachers from across Canada and the United States participated in an online survey, comprising both open- and closed-ended questions, to gauge their pedagogy regarding performance training, perfectionism, and MPA. While the majority of participants reported that students have expressed MPA concerns to them, many noted that they only discuss the issue when students raise it. Virtually all teachers reported that they teach students what to do on stage and how to address performance challenges—in particular memory lapses. Most believe there is a distinction between teaching to play and teaching to perform, yet only 58% said they offer studio classes and 37% hold dress rehearsals. Participants noted a focus on excellence, not perfection, in their pedagogy, but many acknowledged that perfection is an expectation within the field. Comparisons with previous findings on piano students and implications for educators are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.058
GPT teacher head0.281
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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