Investigating Musical Aptitude Examination with a Many-Facet Rasch Model
Abstract
The aim of this study is to show how a many-facet Rasch measurement model (MFRM) can be used for quality control whilst monitoring a musical aptitude examination. The data used in this study was gathered from a musical aptitude examination which was applied in 2019-2020 academic year for selecting teacher candidates to a music education department in one public university in Turkey. In this study, the total scores of musical singing and playing exams were used. The study group of this research is consisted of 164 candidates and five specialists who rated the musical performance of candidates. A three-facet Rasch model was used including student (n=164), rater (n=5), and task (n=2). Data was gathered with fully crossed design. MFRM analysis showed good fit the data. The reliability of separation index for students was very high and it indicated that the musical aptitude examination differentiate among students in terms of their musical performance. The reliability of the rater separation index was found as 0.00 and it suggested that raters rated students’ musical performance with very similar levels of severity/leniency and they were interchangeable. The results of task measure showed that musical singing task is harder than musical playing task. The results of bias analyses showed that there is no bias based on rater by task and rater by student interactions. However, student by task interaction has some bias measures.
Keywords
Many-facet Rasch Model, rater reliability, musical aptitude examination
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