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Record W3203927055 · doi:10.5539/ies.v14n10p116

The Relationships Between Music Performance Anxiety and the Mindfulness Levels of Music Teacher Candidates

2021· article· en· W3203927055 on OpenAlexvenueno aff
Birsen Jelen

Bibliographic record

VenueInternational Education Studies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessPsychologyPianoAnalysis of varianceAnxietyPearson product-moment correlation coefficientDevelopmental psychologyClinical psychologyPositive relationshipSocial psychologyArt

Abstract

fetched live from OpenAlex

In this study the relationships between the Music Performance Anxiety (MPA) levels and mindfulness levels of Music Teacher Candidates (MTC) were investigated. A large sample of undergraduate students (N = 524) from seven different universities from around Turkey took place in the study. The data was collected with both Kenny’s MPA inventory and the Five Facets Mindfulness Questionnaire. The Pearson Moments Correlation Coefficient was used in determining the relationships between the MPA and mindfulness levels of the MTC. To determine whether the MPA of students and mindfulness differ in terms of piano lesson achievement and daily piano practice time (DPPT) variables, a variance analysis (ANOVA) and a Kruskal Wallis H test analyses were used. Students’ mindfulness levels were negatively correlated with their MPA levels. Their piano lesson achievement levels had positive relationship with mindfulness and a negative relationship with their MPA. Similarly, their DPPT had a positive relationship with mindfulness and a negative relationship with MPA.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.159
GPT teacher head0.315
Teacher spread0.156 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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