Publication Date

2011-04-18

Availability

Open access

Embargo Period

2011-04-18

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Music Education and Music Therapy (Music)

Date of Defense

2011-04-07

First Committee Member

Stephen F. Zdzinski

Second Committee Member

Edward P. Asmus

Third Committee Member

Nicholas J. DeCarbo

Fourth Committee Member

Gary Green

Fifth Committee Member

Marilyn Neff

Abstract

The purpose of this study was to test a hypothesized model of wind-band intonation, using equipment, instruction and director and student attributes as components. Band directors (N= 5) and their students N= 200) were given a combination of published and researcher designed tests to measure equipment quality, experience, knowledge of instrument pitch tendencies and aural discrimination skills. In addition, each band was video recorded to observe their warm-up, tuning and rehearsal procedures and activities. Spectrum analysis using Praat phonetic analysis software (Boersma & Weenik, 2010) was used to measure wind-band intonation. Structural equation modeling (SEM) using AMOS (Arbuckle, 2008) was the method chosen to analyze and interpret the data. Although the hypothesized model could not be estimated, a model generating approach resulted in a three-factor model describing the effects of instruction and student attributes on wind-band intonation. Model fit was good (χ2 = 3.486, df = 7, p = .837, GFI = .994, CFI = 1.00, RMSEA = .000). The respecified model indicated that instruction and student attributes explain 99.3% of the variance in the dependent variable wind-band intonation. For each SD increase in the latent instruction variable, wind-band intonation increases by .95 a SD. Activities involving aural-based tuning strategies, tuning intervals and chords evidenced higher intonation scores. For each SD increase in the latent student attributes variable, wind-band intonation increases by .16 a SD. This suggests that instrument quality, experience in band and private lessons, and aural acuity combine to affect intonation scores, but these student attributes are less influential than instruction. A supplementary finding revealed that 72.5% of the students n = 145) made at least one error (M = 4.05, SD = 3.76) on the test measuring knowledge of their instrument’s pitch tendencies.

Keywords

intonation; band; spectrum analysis; instruction; harmony; pitch; tuning; model

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