Report prepared by Benjamin C. Helton, Ph.D, Case Western Reserve University
Method
We constructed the method for the current study based on the following research questions:
- What are the current trends in college band and high school musical ensemble enrollment?
- How do ensemble teachers feel about the future of their individual programs in light of predicted drops in enrollment?
- What factors contribute to the differences between college and high school teachers’ perceptions of the current and future health of the ensembles they teach?
These questions were answerable utilizing a survey sent to two groups. The first sample consisted of collegiate band directors who belonged to the College Band Directors National Association (CBDNA). An online survey was sent to the total membership of the organization. The second group represented a random national sampling of high school ensemble directors. The National Federation of State High School Associations (NFHS) sent a similar survey to a random sample of their email database. Ultimately, we received replies from national samples of CBDNA members (n = 293) and high school ensemble teachers (n = 3,095).
Survey Construction
Members of both CBDNA and NFHS developed two different surveys for internal data collection purposes. The two organizations’ initial goals for the survey differed, so some measurements and responses differed slightly between the two surveys. However, we coordinated certain aspects in order to compare certain data points between the two samples. The key comparative psychometric was based on the Positive and Negative Affect Schedule (PANAS) template (Watson et al., 1998). We developed ten items for respondents to rate on a five-point Likert scale to be included on both surveys. The PANAS measured how “optimistic” the respondent felt about the future health of their program.
The two organizations disseminated the surveys independently and we pooled our data once they were collected. We then cleaned the data and ran normality tests to ensure valid inferential analyses and comparisons could be made. As will be seen below, some survey items applied to only one group, so a factor could have been considered for one sample and not the other. For example, NFHS’s survey collected tertiary data related to different types of program support for a purpose separate from this study, but we found those data informative for the purpose of developing advocacy strategies for both groups.
Exploratory Factor Analysis
We calculated participants’ optimism scores by performing an exploratory factor analysis (EFA) on the ten-item PANAS questionnaire given to both populations in order to determine which items shared similar latent constructs. This process reduces measurement error in ordinal data – such as Likert survey responses – and determines which items can be averaged together to create one scalar psychometric score (Miksza & Elpus, 2018). The EFA on the college band director responses a Kaiser-Meyer-Oklin Measure of Sampling Adequacy of .898 and a Bartlett’s Test of Sphericity of χ2 = 1042.50, p < .001. These results indicated a large enough sample (n = 246) for the EFA to be performed and that the items were sufficiently independent to produce accurate factor loadings. This sample adequacy and independence also indicated that the component matrix did not need to be rotated to produce reliable factors. Eight of the ten items shared one strong eigenvalue (λ = 4.76) and the Cronbach alpha for those eight items was α = .86. Those items were then averaged together to produce one optimism score for the college band directors M = 3.25 (SD = .71). The alpha for those same item responses from high school ensemble directors was α = .86 and the measures of central tendency were M = 3.41 (SD = .77).
Results
College Band Directors
Respondents (n = 293) were from every state except for Alaska and New Mexico. The states with the most respondents were Ohio, Pennsylvania, and Texas with eleven each. Respondents were predominantly male (89%) and white (90%). Only 4% identified as African American and 1% identified as Latin@. Ages ranged from 29-77 years old (M = 50, SD = 9.78). Teaching experienced ranged from first year college teachers to more than 20 years of college teaching experience, with 41.9% of respondents having taught more than 20 years.
Of the respondents, 80.5% reported having a concert band, 76.1% had a wind ensemble, 68.3% had an athletic band program, 87.4% had a jazz ensemble, and 17.1% had a modern (pop) band. School locale broke down to 34% of respondents teaching in urban, 34.8% in suburban, and 38.2% in rural settings. 38.1% taught at Research I institutions and 16.3% taught at Research II. 42.3% reported that their institution carried no Carnegie classification. Most respondents (63.2%) taught at public 4-year universities. 18% taught at private religious institutions and 14.4% taught at private secular. 2% taught at community colleges.
Over the last three years, 13.8% reported that a curricular ensemble had been discontinued due to low enrollment. This action was independent of administrative decisions made in response to the COVID-19 pandemic. The general enrollment trends from 2021/2022 to this year (2022/2023) among respondents were as follows:
Table 1
Percentages of Higher Education Enrollment Trend Responses
| Population Trend | Decreased Substantially | Decreased Slightly | Stayed About the Same | Increased Slightly | Increased Substantially |
| Institution | 13.2% | 24.4% | 21.1% | 33.1% | 8.3% |
| Program | 9% | 21.7% | 25.6% | 29.7% | 8.6% |
| Athletic Band | 7.5% | 22.1% | 27.5% | 22.9% | 14.2% |
Note: 5.8% of respondents responded N/A to the Athletic Band Question
Predictably, those respondents who saw a significant decrease in their program enrollment tended to be about .7 points less optimistic than those whose enrollment either stayed the same or increased (p < .001). Optimism scores were significantly higher by about .45 points for participants teaching at private parochial schools compared to those at public four-year institutions (p < .001). We observed a similar significant difference (p < .01) depending on if a participant taught in a 2020 “red” state or “blue” state, with “red” state participants being .23 points more optimistic than participants in “blue” states. Further analysis showed no other significant differences in optimism between subgroups. Notably, there were no significant differences in optimism between different locales (rural, suburban, urban) or a school’s Carnegie research designation.
High School Ensemble Teachers
Teachers from all fifty states responded to the NFHS survey (n = 2,906). Demographics for the sample, along with their school-level data, can be seen in Table 2. In addition to the PANAS, participants also answered questions related to the support the received from their schools and communities on a five-point Likert scale. Using an EFA, we reduced those items into one “support” metric. The EFA on the high school teachers’ support responses returned a Kaiser-Meyer-Oklin Measure of Sampling Adequacy of .940 and a Bartlett’s Test of Sphericity of χ2 = 19,012.22, p < .001. This sample adequacy and independence indicated that the component matrix did not need to be rotated to produce reliable factors. Thirteen of the eighteen items shared one strong eigenvalue (λ = 6.68) and had a Cronbach alpha of α = .90. Those thirteen items were then averaged together to produce one support score for the high school ensemble teachers M = 3.59 (SD = .81).
Table 2
Demographic Percentages of NFHS Survey Participants
| Teaching Assignment | % | Teaching Level | % | Years Teaching | % |
| Band | 41.1 | HS | 39.5 | 1st Year | 3.0 |
| Chorus | 21.1 | Middle | 26.2 | 2-5 | 12.8 |
| Orchestra | 9.3 | Elem. | 25.3 | 6-10 | 16.0 |
| General | 26.0 | K-12 | 9.0 | 11-15 | 13.5 |
| Other | 1.7 | 16-20 | 15.1 | ||
| Missing | .8 | 21-25 | 14.5 | ||
| 26+ | 25.1 |
| School Type | % | School Enrollment | % | Program Enrollment Trend | % |
| Public | 89.9 | 1-250 | 10.8 | Decreased Substantially | 12.9 |
| Private (Parochial) | 5.9 | 251-500 | 27.3 | Decreased | 10.3 |
| 501-1000 | 31.6 | Decreased Slightly | 17.7 | ||
| Private (Secular) | 2.2 | 1001-1500 | 13.8 | Stayed about the Same | 16.3 |
| 1501-2000 | 9.6 | Increased Slightly | 20.7 | ||
| Charter | 2.0 | 2001-3000 | 4.0 | Increased | 8.8 |
| 3001+ | 2.8 | Increased Substantially | 8.7 | ||
| N/A | 4.6 |
Note. These percentages are for the entire sample (n = 2,906). They do not reflect any crosstabulations.
“Support” and “optimism” significant differences (waiting on locale data transformation), but, similar to the CBDNA member responses, few significant differences between optimism with the exception of private/public schools (results not substantial, but significant). Same with feelings of support (private (p) feel about .4 points more supported than their public school counterparts (p < .001). Also notably, respondents who reported a substantial drop in program enrollment tended to feel about .3 less supported than those who reported steady or increasing enrollment (p < .001).
Due to the lack of significant differences between groups, we correlated optimism and feelings of support along with two single-item, summative survey responses. Those correlations can all be seen in Table 3. Notably, all correlations were significant (p < .001) and were low to moderately high. Feelings of support correlated moderately high (r = .678, p < .001) with general satisfaction as a music educator and optimism was only moderately correlated (r = .476, p < .001).
Table 3
Pearson Product Moment Correlations Between Relevant Survey Items
| “I am satisfied with my decision to become a music educator” | “I am satisfied with my role as a music educator” | Feelings of Support | Optimism | |
| “I am satisfied with my decision to become a music educator” | 1 | .781* | .540* | .384* |
| “I am satisfied with my role as a music educator” | .781* | 1 | .678* | .478* |
| Feelings of Support | .540* | .678* | 1 | .496* |
| Optimism | .384* | .478* | .496* | 1 |
Note. * indicates a significant correlation at (p < .001).
References
Miksza, P. & Elpus, K. (2018). Design and analysis for quantitative research in music education. Oxford.
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063-1070. https://doi.org/0022-3514/88/$00.75