Children’s feelings about piano performances across a year of study
Bibliographic record
Abstract
Solo performance is a common experience for children learning to play an instrument, yet the research literature on these experiences is limited, with a focus on older children and adolescents. The purpose of this study was to examine younger children's feelings about performance over the course of a year of study. Forty-one children were interviewed about their piano lessons and performance experiences at the end of two consecutive semesters of study. They also responded to a pictorial scale on their feelings about performance at each interview and again at two piano recitals. Results indicate that children are remarkably consistent in their feelings about performing in piano recitals, with few significant changes over time and context. Correlation analyses indicate changes in the relationships between feelings about performance and certain study variables over time-in particular age, liking of lessons, liking of performing, practice time, and perception of being good at piano. In the fall term, gender and age are significant predictors of feelings about performance, with younger children and boys feeling most positive. In the spring, the findings shift and the only significant predictor is children's liking of piano lessons. Implications and directions for further research 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 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".