Rater fairness in music performance assessment: evaluating model-data fit and differential rater functioning
Abstract
The purpose of this study was to investigate model-data fit and differential rater functioning in the context of large group music performance assessment using the Many-Facet Rasch Partial Credit Measurement Model. In particular, we sought to identify whether or not expert raters’ ( N = 24) severity was invariant across four school levels (middle school, high school, collegiate, professional). Interaction analyses suggested that differential rater functioning existed for both the group of raters and some individual raters based on their expected locations on the logit scale. This indicates that expert raters did not demonstrate invariant levels of severity when rating subgroups of ensembles across the four school levels. Of the 92 potential pairwise interactions examined, 14 (15.2%) interactions were found to be statistically significant, indicating that 10 individual raters demonstrated differential severity across at least one school level. Interpretations of meaningful systematic patterns emerged for some raters after investigating individual pairwise interactions. Implications for improving the fairness and equity in large group music performance evaluations are discussed.
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Expert raters commonly disagree when rating music performance quality.
“Considering how common it is for expert raters to disagree when rating music performance quality (Wapnick et al., 2005; Wesolowski et al., 2015), a future study should certainly use a scale with published psychometric data.”
From Acceptance and commitment therapy for the treatment of music performance anxiety: A pilot study with student vocalists (2017) · cites this paper as Wesolowski et al., 2015
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- Authors
- Wesolowski, B. C., Wind, S. A., & Engelhard, G.
- Affiliations
- University of Georgia (US)
- University of Alabama (US)
- Venue
- Musicae Scientiae
- Publisher
- SAGE Publications
- Published
- 2015-05-22
- Volume
- 19
- Issue
- 2
- Pages
- 147-170
- ISSN
- 1029-8649 (ISSN-L)
- 2045-4147
- OpenAlex
- W2342276252
- Cited by
- 50
- References
- 68
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 3 · 2023: 5 · 2021: 6 · 2020: 2 · 2019: 10 · 2018: 9 · 2017: 7 · 2016: 4 · 2015: 1
- FWCI
- 8.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Musicae Scientiae (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Arts and Humanities › Music › Diverse Music Education Insights
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- music performance assessment, rater severity, model-data fit, school level differences
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