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Record W4408042024 · doi:10.1177/10570837251318019

Performing Music and Performing Teaching: A Pilot Study on the Experiences and Anxieties of Preservice Music Teachers

2025· article· en· W4408042024 on OpenAlexaff
Charlene Ryan, Gina Ryan

Bibliographic record

VenueJournal of Music Teacher Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversité du Québec à MontréalToronto Metropolitan University
Fundersnot available
KeywordsMusic educationPsychologyMathematics educationPedagogyVisual artsArt

Abstract

fetched live from OpenAlex

Anxiety related to music performance and to teaching in non-music fields has been studied extensively; however, anxiety pertaining to the performative roles specific to music teachers, both preservice and inservice, has yet to be considered. This pilot study was designed to take the first steps in examining music education students’ anxieties in the context of preservice teaching. Twenty-seven music education students completed a questionnaire about their preservice teaching experience that included the Kenny Music Performance Anxiety Inventory, modified and divided into two sections. Participants responded to the first section (general life questions) once and the second (performance contexts) three times in direct succession, based on their experiences when performing, teaching, and conducting. No significant differences in anxiety scores were noted across the three contexts, indicating a similar degree of anxiety when performing as a musician and as a teacher. Implications for teacher educators and researchers 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.080
GPT teacher head0.290
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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