Ziyong Lin, A. Werner, U. Lindenberger, A. Brandmaier, Elisabeth Wenger
{"title":"Assessing Music Expertise","authors":"Ziyong Lin, A. Werner, U. Lindenberger, A. Brandmaier, Elisabeth Wenger","doi":"10.1525/MP.2021.38.4.406","DOIUrl":null,"url":null,"abstract":"We introduce the Berlin Gehoerbildung Scale (BGS), a multidimensional assessment of music expertise in amateur musicians and music professionals. The BGS is informed by music theory and uses a variety of testing methods in the ear-training tradition, with items covering four different dimensions of music expertise: (1) intervals and scales, (2) dictation, (3) chords and cadences, and (4) complex listening. We validated the test in a sample of amateur musicians, aspiring professional musicians, and students attending a highly competitive music conservatory (n = 59). Using structural equation modeling, we compared two factor models: a unidimensional model postulating a single factor of music expertise; and a hierarchical model, according to which four first-order subscale factors load on a second-order factor of general music expertise. The hierarchical model showed better fit to the data than the unidimensional model, indicating that the four subscales capture reliable variance above and beyond the general factor of music expertise. There were reliable group differences on both the second-order general factor and the four subscales, with music students outperforming aspiring professionals and amateur musicians. We conclude that the BGS is an adequate measurement instrument for assessing individual differences in music expertise, especially at high levels of expertise.","PeriodicalId":47786,"journal":{"name":"Music Perception","volume":"38 1","pages":"406-421"},"PeriodicalIF":1.3000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Music Perception","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1525/MP.2021.38.4.406","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"MUSIC","Score":null,"Total":0}
引用次数: 0
Abstract
We introduce the Berlin Gehoerbildung Scale (BGS), a multidimensional assessment of music expertise in amateur musicians and music professionals. The BGS is informed by music theory and uses a variety of testing methods in the ear-training tradition, with items covering four different dimensions of music expertise: (1) intervals and scales, (2) dictation, (3) chords and cadences, and (4) complex listening. We validated the test in a sample of amateur musicians, aspiring professional musicians, and students attending a highly competitive music conservatory (n = 59). Using structural equation modeling, we compared two factor models: a unidimensional model postulating a single factor of music expertise; and a hierarchical model, according to which four first-order subscale factors load on a second-order factor of general music expertise. The hierarchical model showed better fit to the data than the unidimensional model, indicating that the four subscales capture reliable variance above and beyond the general factor of music expertise. There were reliable group differences on both the second-order general factor and the four subscales, with music students outperforming aspiring professionals and amateur musicians. We conclude that the BGS is an adequate measurement instrument for assessing individual differences in music expertise, especially at high levels of expertise.
期刊介绍:
Music Perception charts the ongoing scholarly discussion and study of musical phenomena. Publishing original empirical and theoretical papers, methodological articles and critical reviews from renowned scientists and musicians, Music Perception is a repository of insightful research. The broad range of disciplines covered in the journal includes: •Psychology •Psychophysics •Linguistics •Neurology •Neurophysiology •Artificial intelligence •Computer technology •Physical and architectural acoustics •Music theory