Scott E. Russell

Ball State University

Muncie, Indiana

Considerable amounts of time and energy are spent recruiting students into our major disciplines. Students purchase instruments; take private lessons; enroll in junior high and high school bands, orchestras, and choirs; and they may even elect such time-consuming activities as marching band, musical productions, and summer music camps. Secondary school teachers prepare materials that provide musical and theoretical backgrounds for further study, if so desired by the student. These students may go on to achieve varying levels of success at Solo and Ensemble contests. They may perform in Honor Bands, Orchestras, or Choirs. Some may even elect to pursue music as a career by majoring in music in college. Great as their success may be, are they any measure of a student's desire to major in music in college? Which of these diverse experiences is the best predictor for choice of music as a major? How do students select a major at all? Lunnenburg & Lunnenburg (1991) found that high school interests, high school GPA, and college entrance academic achievement scores were good predictors of psychology majors. Sullins, Hernandez, Fuller, & Tashiro (1995) evaluated the relationships among several variables (including gender, science material interest, perceived ability, student expectations, perceived utility of science courses, and future intent to enroll in further science courses) to predict the choice of biology as a major. Moreno & Muller (1999) evaluated the success of a program designed to increase retention in their school's mathematics major by studying gender, race, ethnicity, math SAT scores, and scores in first- and second-semester calculus to predict the number of students who would select majors in mathematics, science, or engineering.

In the field of music education, studies of musical persistence are abundant. When dealing with elementary aged students, Klinedinst (1991) reported that the most effective predictors of student persistence among instrumental students are socioeconomic status, self-concept in music, and academic achievement in math, reading, and scholastic ability. Another study by Hartley (1996) looked at factors involved in retaining beginning instrumental students through the seventh grade year. Among other findings reported in that study, Hartley confirmed that more instructional time leads to an increased retention rate. Finally, Brown & Alley (1983) found that college GPA and first-semester principal instrument jury grade are the two most significant predictors of persistence among music education majors.

For musicians, one key aspect in our background is the depth and quality of private study. Principal instrument experience has been found to be an effective predictor of student persistence in many studies. As mentioned above, Brown & Alley (1983) submitted that the principal instrument jury grade was a significant factor in determining persistence among music education majors. In a 1963 study attempting to find factors involved in music achievement, Colwell found instrumental experience, particularly piano experience, to be an effective predictor for music achievement. Harrison's analyses of music theory grades (1990, 1996) both show principal instrument experience to be an effective predictor of higher theory grades. On the other hand, the relationship between principal instrument (non-piano) instruction and aural skills development has been found to be insignificant (May & Elliot, 1980).

Piano experience has similarly been found to relate to various areas of musical and academic development. Colwell (1963) showed piano training to be the most effective predictor of music achievement. Harrison's two studies (1990, 1996) likewise show some increase in theory scores (particularly keyboard harmony skills) as a result of piano experience. Finally, May & Elliot (1980) show a significant link between the number of years of piano study and aural skills development.

In a study designed to find factors relevant to the selection process of music education as a major, Bergee (1992) reported that most music education students (78%) had chosen their major while attending high school and that their greatest influence was positive encouragement and positive role modeling by their high school music teacher.

The National Association of Schools of Music (NASM, 1996) offers the following advice to high school students aspiring to major in music at the collegiate level: "Performance ability is essential for all musiciansŠ. Keyboard ability is important for the life work of most musicians. Students with keyboard skills have a head start as music majors." But how much study is enough? Is there a relationship between these pre-college musical experiences and the student's choice of major?

While there are studies examining the relationships between musical experience and persistence, or between other background factors and the selection of music as a major, no one has looked at the correlation between musical experience and student's choice of collegiate major. The purpose of this study is to examine that relationship and to attempt to find a model for prediction of collegiate major based upon the factors of principal instrument experience and piano experience.

For the purposes of this study, principal instrument experience is the number of years of pre-collegiate private lessons on the principal instrument (in this case, all Ss are horn students); piano experience is the number of years of pre-collegiate private instruction on piano, and the student's choice of collegiate major is their current major (musical or non-musical) regardless of class standing.

The purpose of this study was to determine the relationship between the amount of pre-collegiate applied lesson experience on horn and piano, and the choice of collegiate major among undergraduate horn students. It is posited that no relationship will exist between applied horn experience and the choice of undergraduate major. Further, no relationship will exist between applied piano experience and the choice of undergraduate major.

Participants

The participants were 16 undergraduate horn students (9 females, 7 males) at a large Midwestern university. All were enrolled in university-level private horn lessons and the Horn Ensemble. Grade levels of Ss ranged from freshman (score of 1 of the Year in School) to 5^th-year seniors (score of 5) with a mean grade level of 2.75.

Tasks and Materials

The survey instrument was constructed by the researcher and consisted of two fill-in questions to determine the number of pre-college years studied on horn and piano, one checklist item to determine current college major, and two categorical items to determine gender and current grade level. The survey was administered to all students at a rehearsal of the Horn Ensemble, of which all Ss were members. The survey instrument (Survey of Private Lessons and College Major) is attached in Appendix A.

Independent Variables

Two factors were measured: number of years of pre-collegiate horn lessons and number of years of pre-collegiate piano lessons. These interval values were self-reported on the survey instrument by the Ss.

Dependent Variables

Current major was selected from among a list of the school's complete undergraduate offerings of music majors (music composition, music education, music performance, and music engineering technology), a subject-specified non-music major, or an indication that they were undecided. Double majors were instructed to check both majors. No Ss reported being undecided and 2 Ss listed two majors, indicating that they carried a double major. Of these two Ss, one listed a music major (music education) and a non-music major (mathematics); the other listed two music majors (education and performance). A determination had to be made as to how to roster these two Ss. It seemed appropriate to classify them as only one of their selected majors based on their classroom and other experiences. The first S (music education & math) is receiving all of the musical training of a music education major and is therefore classified as such. Likewise, the second S (music education & performance) is receiving training in both fields; however, the courses in the performance curriculum are not unique to that field. All first-year education majors and performance majors take the same lessons and theory classes. The courses that set the majors apart are the introductory courses in music education. Since this S is participating in the music education curriculum, she is identified as a music education major for the purposes of data analysis.

Data Analysis

This study used a MANOVA to examine patterns between years of horn study and choice of major, and years of piano study and choice of major. Gender and year in school were also factored into the analysis. Post hoc Bonferroni and Tukey tests examined the significant relationship to determine which level or levels of each factor merited a significant relationship with the choice of major. All tests were subjected to the.05 level of significance.

Results

The means of PIANOYRS and HORNYRS of each MAJOR group were as follows: Non-Music majors averaged 1.00 years of piano lessons and 3.00 years of horn lessons; Music Education majors, 4.36 years of piano and 3.23 years of horn; and Music Performance majors, 10.50 years of piano and 2.50 years of horn.

There were no Composition majors in the study and the single MET student took no pre-collegiate horn lessons and 8.00 years of piano. The MET major was therefore dropped from the analysis because no Post Hoc results could be run with only one student in the MET major category (two or more Ss are required in each category for the Post Hoc tests to be completed). (See Table 1: Comparison of Means of PIANOYRS and HORNYRS by MAJOR)

A MANOVA was run to determine the relationships among HORNYRS, PIANOYRS, and MAJOR. To run the MANOVA, HORNYRS and PIANOYRS were considered to be "dependent variables" because they were measured in interval data, MAJOR, GENDER and SCHLYEAR were "fixed variables" because they were measured with nominal data. The results show that PIANOYRS is significantly related (p<.05) to all three of the fixed variables GENDER, SCHLYEAR, and MAJOR. No significance was found between HORNYRS and any of the fixed variables. (See Tables 2 and 3: MANOVA Tests of Between-Subjects Effects with HORNYRS and PIANOYRS as Dependent Variables.)

While there were significant interactions when calculating mean number of years of piano study along lines of gender and year in school, those did not increase the significance beyond the p < .05 level.

Post Hoc Bonferroni and Tukey analyses confirm that significant differences exist between all three MAJORS (performance, education, and non-music) on the factor of PIANOYRS. (See Table 4)

Discussion

The two null hypotheses stated that no relationship would exist between applied horn experience and the choice of undergraduate major; and further, that no relationship would exist between applied piano experience and the choice of undergraduate major. The data indicate that there is no directional relationship between the number of years of private horn study and the choice of a collegiate major. It does, however, indicate a positive relationship between the number of years of private piano study and the choice of major. Non-major students studying horn had the lowest mean number of years of piano study (1.0); music education majors had a higher mean (4.4); and music performance majors were higher still (10.5). This would seem to indicate that piano study is essential to developing musicians, and even more so to developing performers.

Suggestions for conducting further study would certainly include a larger sample size. The sample in this study represents nearly the entire population of the horn studio at the university but does not attain a size of real statistical significance. Further studies should find a larger population of horn students (by region, or by state) to see if the same significance of piano study is observed. Other studies might also compare mean years of piano study of horn players with performers on other instruments to determine any interaction based on principal instrument. Also of interest might be the number of students graduating with their respective degrees instead of evaluating students whose degrees are still in progress. The sample cited here could indicate a good model for recruiting students willing to major in music, but does nothing to suggest that these students will continue in their studies until graduation.

References

Bergee, M.J. (1992). Certain attitudes toward occupational status held by music education majors. Journal of Research in Music Education, 40(2), 104-113.

Brown, A. & Alley, J.M. (1983). Multivariate analysis of degree persistence of undergraduate music education majors. Journal of Research in Music Education, 31 (4), 271-281.

Colwell, R. (1963). An investigation of musical achievement among vocal students, vocal-instrumental students, and instrumental students. Journal of Research in Music Education, 11, 123-130.

Ernest, D.J. (1970). The prediction of academic success of college music majors. Journal of Research in Music Education, 18 (3), 273-276.

Hartley, L.A. (1996). Influence of starting grade and school organization on enrollment and retention in beginning instrumental music. Journal of Research in Music Education, 44 (4), 304-318.

Harrison, C.S. (1990). Relationships between grades in the components of freshman music theory and selected background variables. Journal of Research in Music Education, 38 (3), 175-186.

Harrison, C.S. (1996). Relationships between grades in music theory for nonmusic majors and selected background variables. Journal of Research in Music Education, 44 (4), 341-352.

Klinedinst, R.E. (1991). Predicting performance achievement and retention of fifth-grade instrumental students. Journal of Research in Music Education, 39 (3), 225-238.

Lunnenborg, C.E. & Lunnenborg, P.W. (1991). Who majors in psychology? Teaching of Psychology, 18 (3), 144-148.

May, W.V. & Elliot, C.A. (1980). Relationships among ensemble participation, private instruction, and aural skill development. Journal of Research in Music Education, 28 (3), 155-161.

Moreno, S.E. & Muller, C. (1999). Success and diversity: The transition through first-year calculus in the university. American Journal of Education, 108 (1), 30-57.

National Association of Schools of Music. (1996). FAQ: Potential Students and Their Parents: "How should I best prepare to enter a conservatory, college, university as a music major?" Retrieved September 30, 2001, from http://www.arts-accredit.org/nasm/advisor_nasm.html

Sullins, E.S., Hernandez, D., Fuller, C., & Tashiro, J.S. (1995). Predicting who will major in a science discipline: Expectancy-value theory as part of an ecological model for studying academic communities. Journal of Research in Science Teaching, 32 (1), 99-119.