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An examination of the influence of band director teaching style and personality on ratings at concert and marching band events
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by Timothy Groulx.
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b University of South Florida,
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Dissertation (PHD)--University of South Florida, 2010.
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ABSTRACT: This descriptive correlational study examined the relationship between high school band directors' teaching style and personality and their ratings in marching and concert band festivals using the Five-Factor Model of personality and Gumm's Music Teaching Style Inventory. The sample (N=176) consisted of 46% of all high school band directors in Florida. Criterion variables included marching and concert festival ratings, state concert band ratings, Florida Marching Band Coalition marching competition scores, frequency of attendance of these last two events, and the balance between marching and concert band. Predictor variables included thirty personality facets and eight teaching styles. Four demographic variables included gender, experience, academic degree, and primary instrument. One predictor, Time Efficiency, stood out as having particularly strong correlations with all of criterion variables. Regression models produced the following findings: 23% of the variation in concert band ratings can be explained from Time Efficiency, Immoderation, Music Concept Learning Assertiveness, and Nonverbal Motivation; 22% of the variation in marching band scores can be explained by Time Efficiency, Music Concept Learning, Imagination, Modesty, Cheerfulness, and Anxiety; 20% of the variation in participation in state Florida Bandmasters Association concert band festival participation can be explained by Time Efficiency, Positive Learning Environment, Immoderation, Music Concept Learning, Group Dynamic, and Assertive Teaching, and 11% of the variation in FMBC competitive marching band event attendance can be explained by Time Efficiency, Nonverbal Motivation, Dutifulness, and Modesty. Most subjects (84.3%) were balanced, while the remaining 15.7% were marching oriented. There was no significant difference in marching ratings between groups, although balanced subjects scored significantly higher in concert band and attended significantly fewer marching competitions. A discriminant function selected four predictor variables with a significant effect: Assertiveness, Immoderation, Adventurousness, and Emotion (Wilks' lambda = .84, chi-square = 23.42, df = 4, p
Advisor: C. Victor Fung, Ph.D.
t USF Electronic Theses and Dissertations.
An Examination of the Influence of Band Di rector Teaching Style and Personality on Ratings at Concert and Marching Band Events by Timothy J. Groulx A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Center for Music Education Research School of Music College of The Arts University of South Florida Major Professor: C. Victor Fung, Ph.D. John C. Carmichael, Ph.D. Carlos X. Rodriguez, Ph.D. David A. Williams, Ph.D. Date of Approval: May 7, 2010 Keywords: music, music education, festival ratings, competition, social psychology Copyright 2010, Timothy J. Groulx
Dedication This research is dedicated in part to my loving wife, Shirdellah who has supported me throughout my entire doctoral program, a nd patiently endured my many long hours of writing. It is also dedicated in part to my beautiful daught er Claire who has kept my spirits high throughout the entire process a nd reminded me of what is most important. Finally I also dedicate this in part to my parents, Dennis and Mary Groulx, who have always believed in me, supported me, and encouraged me to pursue my dreams.
Acknowledgments I would like to thank my major professor and a person who I have considered as a mentor throughout my doctoral program, C. Victor Fung. His knowledge, experience, willingness to help, and breadth and depth of knowledge have been invaluable for the past four years, especially during the disse rtation process. I also wish to thank my committee members, John C. Carmichael, Carl os X. Rodriguez, and David A. Williams for their input, professional perspectives research acumen, and advice on both content and form. I have come far as an academic writer because of the knowledge, high standards, and detail-oriente d perspective of these profe ssors. I wish to thank the members of the Center for Music Education Re search at USF who have also helped me develop my thoughts and ideas which grew into the present study. Last I wish to thank all of the hard-working high school band direct ors in the state of Florida who not only participated in my study but did so amidst the burdens of running their successful high school band programs which are a part of why th is state is a rich place for the profession of music education.
i Table of Contents List of Tables iv List of Figures vi Abstract vii Chapter 1: Introduction 1 Theoretical Framework 4 Purpose 5 Research Questions 5 Significance of the Study 6 Operational Definition of Terms 7 Limitations 9 Chapter 2: Review of Literature 10 Factors Affecting Band Ratings at Festivals and Competitions 10 Director Qualities/Factors 11 Aspects of the School and the Band 13 The Rating of Bands 19 Synthesis of Band Ratings 21 Personality and Music Educators 22 Personality Profiles of Music Educators 28 Implications of Myers-Briggs Dimensions in Music Educators 32 The Introversion/Extraversion dimension 32 The Sensing/Intuitive dimension 34 The Thinking/Feeling dimension 35 The Judging/Perceiving dimension 35 Personality Synthesis 36 Music Educators and Teaching Styles 37 Teaching Style and Ratings 38 GummÂ’s Model of Teaching Style 39 Other Models of Teaching Style 42 Teaching Style Synthesis 44 Synthesis of Literature and Conclusions 45
ii Chapter 3: Methodology 47 Population and sample 47 The Variables 47 Criterion variables 48 Marching Ratings 50 Concert Ratings 51 Competitive Marching Ratings 51 State Concert Band Ratings 51 Marching Competition Attendance Frequency 52 Mean High Score in Marching Competitions 52 State Concert Festival Attendance Frequency 52 Balance 52 Predictor Variables 53 Demographic Variables 54 Gender 54 Experience 54 Education 54 Instrument 54 The Survey Instrument 55 Data Collection 59 Data Analysis 60 IPIP-NEO 60 MTSI 60 District FBA Concert and Marching Band Ratings 60 Competitive Marching Band Events 61 State FBA Concert Band Events 61 Analysis of the Variables 61 Chapter 4: Results of the Da ta Analysis 64 The Research Questions 81 Chapter 5: Summary, Discussion, Conclu sions, and Recommendations 95 Summary 95 Discussion 97 The Preliminary Analysis 98 Research Question 1 103 Research Question 2 105 Research Question 3 107 Research Question 4 108 Research Question 5 109 Conclusions 111 Implications 120 Recommendations for Further Research 122 References 125
iii Appendices 138 Appendix A Descriptive Statisti cs for Criterion Variables by Gender 139 Appendix B Descriptive Statisti cs for Criterion Variables by Academic Degree 140 Appendix C Descriptive Statisti cs for Criterion Variables by Instrument 141 Appendix D Descriptive Statisti cs for Predictor Variables by Gender 143 Appendix E Descriptive Statisti cs for Predictor Variables by Academic Degree 144 Appendix F Descriptive Statisti cs for Predictor Variables by Instrument 145 Appendix G BalanceFrequencies and Percentage by Gender 149 Appendix H BalanceFrequencie s and Percentage by Academic Degree 150 Appendix I BalanceFrequencies and Percentage by Instrument 151 Appendix J Inter-item correlati ons for Teaching Styles 152 Appendix K Inter-item correlati ons for Personality Facets 154 About the Author End Page
iv List of Tables Table 1 Responses Frequency and Percentage by Florida Bandmasters Association Districts 65 Table 2 InstrumentsFrequenc ies and Percentage 66 Table 3 Descriptive Statistics for Criterion Variables 67 Table 4 Descriptive Statistics for Predictor Variables 69 Table 5 Reliability Data (CronbachÂ’s ) for the Music Teaching Style Inventory 71 Table 6 Item-Total Correlations with Teaching Styles for the Music Teaching Style Inventory 72 Table 7 Reliability Data (CronbachÂ’s ) for the IPIP-NEO Personality Facets 73 Table 8 Item to Personality Facet Correlations for the IPIP-NEO 75 Table 9 Reliability Data for Band Ratings 76 Table 10 Correlations for Criterion Variables with Experience and Academic Degree 76 Table 11 Pearson Product-Moment Correlations for Criterion Variables and Predictor Variables ( n in parentheses) 78 Table 12 Correlations Between Teaching Styles and Personality Facets 80 Table 13 Stepwise Regression and ANOVA for Band Ratings and Predictor Variables 82 Table 14 Regression Coefficients fo r Predictor Variables associated with Criterion Variables 84
v Table 15 Stepwise Regression and ANOVA for State Concert Attendance and FMBC Attendance 85 Table 16 Regression Coefficients fo r Predictor Variables associated with Criterion Variables 87 Table 17 Descriptive Sta tistics of Criterion Vari ables by Balance 87 Table 18 Univariate F-tests of Crit erion Variables on Balance 89 Table 19 Descriptive Sta tistics of Predictor Vari ables by Balance 91 Table 20 Difference of Group Means Between Balanced and Marching Oriented Subjects 92 Table 21 Discriminant Function Anal ysis of Balance (Stepwise Entry Method) 93 Table 22 Summary of Predictors in cluded in Regression Models and Discriminant Function 112
vi List of Figures Figure 1 KeirseyÂ’s Temperaments w ith Myers-Briggs Personality Types 23 Figure 2 The Five Factor Model of Personality: Dimensions and Facets 25 Figure 3 FBA Concert Rating Conversion Example 50 Figure 4 FBA Marching Rating Conversion Example 50
vii An Examination of the Influence of Band Di rector Teaching Style and Personality on Ratings at Concert and Marching Band Events Timothy J. Groulx ABSTRACT This descriptive correlati onal study examined the relationship between high school band directorsÂ’ teaching style and personality and th eir ratings in marching and concert band festivals using the Five-Factor Model of personality and GummÂ’s Music Teaching Style Inventory. The sample ( N= 176) consisted of 46% of all high school band directors in Florida. Criter ion variables included marching and concert festival ratings, state concert band ratings, Florida Marc hing Band Coalition marching competition scores, frequency of attendance of these last two events, and the balance between marching and concert band. Predictor variable s included thirty personality facets and eight teaching styles. Four demographic vari ables included gender, experience, academic degree, and primary instrument. One predictor, Time Efficiency, st ood out as having particularly strong correlations with all of criterion variable s. Regression models produced the following findings: 23% of the variation in concert band ratings can be explained from Time Efficiency, Immoderation, Music Concept Learning Assertiveness, and Nonverbal Motivation; 22% of the variation in marc hing band scores can be explained by Time Efficiency, Music Concept Learning, Imagin ation, Modesty, Cheerfulness, and Anxiety;
viii 20% of the variation in participation in st ate Florida Bandmasters Association concert band festival participation can be explai ned by Time Efficiency, Positive Learning Environment, Immoderation, Music Concept Learning, Group Dynamic, and Assertive Teaching, and 11% of the variation in FMBC competitive marching band event attendance can be explained by Time Effici ency, Nonverbal Motivation, Dutifulness, and Modesty. Most subjects (84.3%) were ba lanced, while the remaining 15.7% were marching oriented. There was no significan t difference in marching ratings between groups, although balanced subjects scored significantly higher in concert band and attended significantly fewer marching competitions. A discriminant function selected four predictor variables w ith a significant effect: A ssertiveness, Immoderation, Adventurousness, and Emotion (WilksÂ’ = .84, 2 = 23.42, df = 4, p <.001) which was able to successfully predict group membership 72.3% of the time. Recommendations include emphasizing the concert band as the core and playing concert music all year. Directors may benef it from being cognizant of their personalities and teaching styles which may enable them to modify their behavior and practices when appropriate to be more effective teachers.
1 Chapter 1: Introduction Music educators define success a number of different ways, one of which is by the success of their students. For high school band directors, one fo rm of student success is through a highly polished and artistic performance, especial ly if it is recognized as such by qualified critics or judges (Burnse d, Hinkle, & King, 1985; Davis, 2000; Dawes, 1989; Stitt, 1997; Stuber, 1997). Ac hieving this may provide th e director with intrinsic benefits such as artistic fulfillment and pride as well as extrinsic benefits such as awards, admiration, recognition, fame, promotion, and in some cases greater job security. Success in a performance can also be measured in a number of different ways including the enthusiasm of audience applause, positive reviews, high ratings at adjudicated performances, or through a shared awarene ss by the students and di rector that a great performance has taken place. In the pursuit of excellence, many as piring band directors who have not yet attained the highest levels of musical achievement strive to understand what differences exist between themselves and those director s who have already ach ieved it. There are numerous variables among band programs such as the type, size, and location of their school, funding, the value students place on musi c, quality and support of administration, community support, and the experience and ed ucation of the band di rector (Beaver, 1973; Dawes, 1989; Davis, 2000; Goodstein, 1984; Goodstein, 1987; Hewitt 2000; Rickels, 2008; Washington, 2007). Many of these factor s have already been the subject of research, although much work remains to be done before there are consistent and
2 complete data on all of these factors. Bo th director-related f actors and school-related factors can influence band ratings, although rese arch indicates director factors are more closely associated with the vari ability in scores (Groulx, 2009). The literature review (Chapter 2) re veals how some fact ors influence band programs and band achievement, although it also reveals where there are gaps in the body of research. Such areas that have received less attention include how the personality and teaching style of the director affect the achie vement of band. These factors are not easy to casually observe, and are somewhat more difficult to measure quantifiably when compared with factors such as school enro llment, years of band director experience, number of students in the pr ogram, or percentage of st udent retention in bands. A teacherÂ’s personality may have a great d eal of influence over his or her ability to thrive professionally and teach and inspire students effectively. While research on teacher recruitment shows no concern for aspe cts of personality or character, the public believes personal characteristics such as pers onality and ethics are critical in a teacher. Deeply ingrained traits, attit udes, and beliefs are unlikely to change significantly during a four or five year undergraduate teacher educ ation program (Colwell, 2006). Psychologists agree that fundamental personality traits do not change once a person reaches adulthood (McCrae & Costa, 2003), although an awareness of personality traits and how they affect professional performance may help a teacher overcome any possible negative effects. A band directorÂ’s teaching style may be more easily changed. Most often a music educator teaches the way in which they themselves were taught, despite years of undergraduate education. However, it is possible to change and better balance teaching styles with careful reflection and understa nding of oneÂ’s own strength s and weaknesses (Fontana,
3 1977; Fontana, 1986). Teaching style can dir ectly affect student learning in the classroom, and consequently may affect achie vement in performance (Gumm, 2003a). It is therefore important to determine if th ere is a correlation between band achievement and aspects of teaching style and personality. I do not consider the pursuit of high ratings to be a valuable end in itself. While the competitive and adjudicated performances are considered sources of pride and motivation to achieve for band students (Austin, 1988; Burnsed & Sochinski, 1983; LaRue, 1986), an excessive amount of competiti on may be an indicator of ratings as a priority over broader music learning goals a nd a perception that mu sical self-worth is based on how the band is rated (Austin, 1990; Hayslett, 1992; Temple, 1973). Croft (1984) describes how these as Â“trophy seek ersÂ” focus excessively on their Â“musical sportÂ” yet pay little to no attention to th eir concert band programs which achieve much lower levels of success. Some directors may spend the entire school year working on three pieces of music which are to be performed in the spring for a concert festival, or a single halftime show for marching band. This ma y lead students to learn music to a high level of technical perfection but diminish the musical and expr essive aspects of it. This also may limit studentsÂ’ exposure to a small number of pieces which they are capable of perfecting rather than teachi ng appreciation of music, important music concepts, and exposing them to a wide variety of good musi cal literature (Battis ti, 1989; Davis, 2000; Dawes, 1989; Laib, 1984; Rickels, 2008; Temple, 1973). Focusing on perfecting a smaller amount of literature rather than studying a wider va riety of literature also may result in studentsÂ’ reduced success in sight-reading (Harris, 1991).
4 Theoretical Framework In this research I examine how band dire ctorsÂ’ personalities and teaching styles affect the success of their ba ndsÂ’ performances. Personality is represented by personal characteristics of the subject described using th e thirty facets of the Five-Factor Model of personality consisting of openness to expe rience, conscientiousness, extraversion, agreeableness, and neuroticism, which is described in detail in the review of literature (Chapter 2). Teaching style is examined us ing GummÂ’s model which includes a subjectÂ’s strengths in eight different modes of inst ruction. The measure of performance success used here is band festival ra tings and attendance frequency. A fundamental premise of this research is aspects of a teacherÂ’s personality can influence the quality of learni ng in his or her classroom. Educ ation research supports this using personality types systems such as the Five-Factor Model (Chamorro-Premuzic, Furnham, & Lewis, 2006; Emmerich, Job, 2004; Rock, & Trapani, 2006; Zhang, 2007), as well as the Myers-Briggs Type Indicator (Roberts, Har lin, & Briers, 2007; Rushton, Morgan, & Richard, 2007). There is also specific research on personality types and how they influence a music educatorÂ’s teach ing effectiveness, (Donovan, 1994; Krueger, 1976; Lewis, 1998; Lutz, 1963; Teachout, 2001), as well as personality research which specifically focuses on band directorsÂ’ teaching effectiveness (Bulloc k, 1974; Stitt, 1997; Westbrook, 2004). The literature also supports th e idea that teaching style can affect the way a teacher prepares his or her classes or ensembles and consequently influence student achievement or festival ratings (C ostello, 2005; Davis, 1998; Dunn & Frazier, 1990; Gumm, 2003b; Gumm, 2004a; Kelly, 197 2; Liberman, 1986; Yarbrough, 1998). Both of these factors are examined here to de termine their relationship to festival ratings.
5 Purpose The purpose of this research is to exam ine the relationship between aspects of high school band directorsÂ’ teach ing style and personality and the directorÂ’s achievement in marching and concert band festivals. Th is research may help illuminate the relationships among teaching style, personalit y, and achievement in musical performance. This research may also enhance the bodies of personality and teaching style research in relation to active high school instrumental music educators, and may also hold implications for personality types and teaching styles which are predictors for success for all music educators. Research Questions There are five questions which are examined in this research. These questions examine the relationships between teaching style, personality, and achievement in marching and concert band festivals, as well as the relation of personality and teaching style to the directorÂ’s balan ce of marching and concert band. 1. What kinds of relationships exist be tween band directorsÂ’ personalities or teaching styles and their concert band ratings? 2. What kinds of relationships exist be tween band directorsÂ’ personalities or teaching styles and their marching band ratings? 3. In what ways do band directorsÂ’ personalities or teaching styles contribute to the number of state concert band events in which their bands participated? 4. In what ways do band directorsÂ’ personalities or teaching styles contribute to the number of competitive marching band events in which their bands participated?
6 5. In what ways do band directorsÂ’ personalities or teaching styles contribute to the balance between marching and concer t band participation and scores? Band director characteristics (teaching style and personality) represent the predictor variables which are correlated to thei r effect on the criterion variables, contest ratings (marching band and concert band). The population in this st udy is all public high school band directors in Flor ida who direct both marching and concert band programs. Significance of the Study This research may help fill gaps in knowledge about the personality of active high school band directors. It would also help to establish a broader and more unified body of research based on GummÂ’s model of teaching style and how teaching styles may affect band ratings. It would also make a connection between personality and teaching style and how these may correlate with success at concer t and marching band festivals. Finally, this research would determine if there are specific personality traits or teaching style traits which correlate with or predict a band dire ctorÂ’s focus on marchi ng band, concert band, or balance between th e two responsibilities. Published research on GummÂ’s model of teaching style is limited and diverse due to the recency of its development and publica tion. Due to the nature of the different teaching styles, it seems that a teacherÂ’s personality may have an effect on which teaching styles he or she may prefer and needs to be investigated. Â“A crucial next step in this line of research has been to find the effect of personality on music teaching styleÂ…Â” (Gumm, personal communication, May 20, 2009). Th ere is also a body of research which may be classified as pertaining to teachi ng style prior to GummÂ’s model, although the
7 topics are rather diverse a nd do not center on a single, organized theory or model of teaching style. Rather, each individual study is based on its own theoretical constructs. Most of the research into personality has focused on music education students and applied studio teachers, and the few studi es which did involve middle and high school band directorsÂ’ personalities have had small sample sizes (Stitt, 1997 had nine, Stuber, 1997 had twenty, Westbrook, 2004 had fifteen), wh ich limits the genera lizability of their studies. Another shortcoming of the existing l iterature on personality research is that research on music education students may not be generalized to act ive music educators; not all music education majors become musi c educators. The liter ature on professional teachers mostly focuses on applied studio inst ructors at the college level, which also cannot safely be generalized to K-12 music educators. Applied instructors are typically responsible for highly specialized instruc tion on a single instrument in a one-on-one setting, and often see fewer than twenty st udents per week. High school band directors work with younger students typically in large-group settings. The high school as a working environment is also different fr om a college or university as a working environment. The findings of the research on applied studio teachers is also difficult to correlate even within th e group itself, as Kemp (1996) discussed the numerous differences between typical personalities of pianists, vocalists, brass players, woodwind players, string players, and perc ussion players (among others). Operational Definition of Terms The term Â“festivalÂ” in this research will refer to adjudicated band performance events. Currently the Florida Bandmasters A ssociation (FBA) refers to these as Music Performance Assessments, or MPAs, although th is is a relatively new term and readers
8 may likely be familiar with the more universal term Â“festival.Â” There are both concert and marching band festivals in Florid a at the district level, spons ored by the FBA, as well as a state concert band festival. Th ere is a state marching band fe stival, although it is run by the Florida Marching Band Coalition, or FMBC, and not the FBA. This state marching band festival and the related FMBC-sponsored regional events utilize a different rating system. Instead of the five categories util ized by the FBA, FMBC assigns a numerical score between 40 and 100 which is a composite of several judgesÂ’ scores rating the band on different aspects of their performances. The term Â“ratingÂ” refers to the final sc ore or division a band is given based on the individual scores awarded by the severa l judges who are adj udicating the band. A marching band rating is composed of two music judges, a marching and maneuvering judge, and a general effect judge. A concer t band rating is composed of three music judges and a sight-reading judge. In this study, Â“ratingÂ” is us ed to refer to the judgesÂ’ evaluations of bands at festivals. The term Â“balanceÂ” used in this research re fers to a categorical variable which is a researcher-created exploratory construct wh ich indicates which of three categories a subject fits based on marching and concert ba nd ratings and participation. This idea of examining how a director balances respons ibilities was examined by Head (1983) who referred to this as emphasis but included director focu s but not achievement. This represents how the subjectÂ’s band ratings are balanced: earning higher ratings and participating in extra concert band events without the same efforts in marching band, earning higher ratings and part icipating in extra marching ba nd events without the same
9 efforts in concert band, or balanced be tween the two. The categories are labeled marching-oriented concert-oriented and balanced. Limitations One possible limitation of this study is the reliabili ty of district festival ratings as a basis to determine success. Another limitati on is that fatigue ma y affect accuracy of responses due to the number of questions in the survey instrument. Traditional limitations of personality research may also arise wher e some subjects may answer questions in a fashion they believe is more professionally desirable rather than giving honest answers which truly reflect th eir personalities.
10 Chapter 2: Review of Literature An examination of band director pers onalities, teaching styles, and how they affect performance quality requires investiga tion into three distinct bodies of existing research. There has been a grea t deal of research done on th e topic of personality, and a number of researchers have also examined va rious factors which affect ratings at band festivals. Research in teachi ng style has gone on for some time, although it has not been a unified and organized concept until relatively recently. First I discuss the research which pertains to band ratings. The next secti on focuses on personality research in music education, followed by the relatively recen t body of teaching style research. Factors Affecting Band Ratings at Festivals and Competitions There are three major themes that emerge in the published studies regarding the factors which influence the ratings of bands. The first category to be examined here includes factors related to the band director such as teaching expe rience and level of education. The second major category in cludes factors which may influence band performance aside from the director, such as the size of the ba nd and school, factors pertaining to students, budget and finances, custom marching shows, assistant directors and staff, use of rehearsal time, success at marching band versus concert band, frequency of festival attendance, as well as other factors. A third line of research examines the contest scores themselves; such as the reliab ility of judging and the criteria for justifying a given score.
11 Director qualities/factors Easily observed and measured factors pert aining to the band director include the directorÂ’s highest degree ear ned, teaching experience, and te nure at the current school. Beaver (1973), Dawes (1989), Davis (2000) Fosse (1965), Goodstein (1984), Maxwell (1970), Mann (1979), Saul (1976), and Washington (2007) all found a positive correlation between more advanced degrees and higher-achieving bands. While causality cannot be determined from these correlati ons, it may be speculated that those band directors who are ambitious and industrious are more likely to both earn an advanced degree and have a band which earns high ra tings. Dawes (1989), Davis (2000), DeCarbo (1986), Fosse (1965), Head (1983), Maxwe ll (1970), Mann (1979), Saul (1976), and Washington (2007) found festiv al ratings improve with increased band director experience, although Rickels (2008) found a co rrelation of only .02 (non-significant) between director experience and ratings. Dawes (1989) found competitions were of greater interest to younger directors than older directors. Less experienced and younger directors attended a larger number of competitions than older, more experienced directors. The amount of time and number of days the director spends rehearsing the band can affect ratings. Davis (2000) studied rehearsal schedules and strategies of different band directors to find which aspects correlate d with higher ratings. The bands in this study were rated using the five-category rating scale which is used in Florida as well as many other states (I-superior, IIexcelle nt, IIIgood, IVfair, Vpoor). He found specific rehearsal strategies (such as focusing on marching or music fundamentals, rhythm counting patterns, etc.) did not significantly affect marching band scores,
12 although superior bands were f ound to practice one to three h ours per day, two to four days per week. This is simply a statement of the practices of s uperior marching bands, not a correlation, and is not es pecially informative as there is a great deal of difference between practicing one hour per day twice a we ek and practicing three hours per day four days per week. Neither Davis (2000) nor Ri ckels (2008) found signifi cant correlations between rehearsal frequency and ratings or length of rehearsal and ratings. Having a band camp was found to correlate positively with improved marching band ratings, although the improvement was not statistically significant. Goodstein (1984, 1987) examined band di rectors from the standpoint of leadership characteristics using a leader ship behaviors measurement instrument developed by Hersey and Blanchard (the L eadership Effectiveness and Adaptability Description Self-Test). He found leadership behaviors were strikingly similar between a selected group of 99 successful band direct ors and a group of 63 randomly selected band directors. Another aspect of band di rectors which correlates to band achievement and student musicianship is motivation. Using the Motivation Analysis Test (MAT), the combination of Â“conscious concern for secu rityÂ” and Â“subconscious concern for home and parentsÂ” were statisti cally significant predictors of ensemble performance. Additionally, Â“subconscious con cern with ethical valuesÂ” wa s a statistically significant predictor of student achievement on the Ho ffer and Long Musicianship Test (Caimi, 1981).
13 Aspects of the School and the Band Beaver (1973), Caimi (1981), Davis (2000), Fosse (1965), Goodstein (1984, 1987), Rickels (2008), and Saul (1976) found the size of th e school from which the band comes significantly affected scores at ma rching band festivals, and the number of students in the band program showed a signi ficant positive correlation with band ratings. DavisÂ’ study of Georgia high school bands also showed that the smallest division of schools (Class A) showed only 25% of their bands earning superior ratings, whereas the largest division (Class AAAA) yielded approxi mately 75% superiors. The size of the band was also correlated with higher ratings. More than 90% of bands larger than 125 members earned superior ratings. There was a significant difference between the mean festival scores of bands in the largest schools ( n = 28, M = 86.51) and the smallest divisions of schools ( n = 6, M = 80.23). Harris (1991) found a diffe rent result that the size of the band had a very low correlation ( r = .05) with sight-reading scores at concert band festivals. Washington (2007) found aspect s pertaining to students and the school were the most significant contributing group of factor s to a bandÂ’s overall festival ratings (combining concert and marching), more so than the directorÂ’s background, teaching practices, or how he/she administrates the ba nd program. Additionally, there is a positive correlation between student achie vement in band and student levels of musicianship as measured by the Long-Hoffer Musicianship Te st (West, 1985). Harris (1991) found the percentage of 11th and 12th graders in the band had a signi ficant positive correlation with sight-reading scores at concert band festival ( r = .323, p < .01 and r = .400, p < .01, respectively), and there is a negative correlation between 9th graders and sight-reading
14 scores ( r = -.364, p < .01). The most influential student-b ased factor in this research on factors influencing sight-readi ng scores was the percentage of students in the band who took private lessons ( r = .426, p < .01), which Washington (2007) also found to be a significant contributing fact or to a bandÂ’s overall succe ss at marching and concert festivals. Student contributi ons to the decision-making pr ocess regarding expressive elements of the music did not significantly affect band performance quality (Petters, 1976). A band budget may include funds for profe ssionally written marching band drill and music, hiring additional instructors to assist with the band, purchasing higher quality instruments, and attending festivals a nd competitions. Goodstein (1984, 1987) and Washington (2007) found the amount of mone y a band was able to raise showed significant positive correlations with their ma rching and concert ratings. The factors with the strongest positive correlation with band ratings were money brought in through fundraising by students and parents, followed by money collected through student fees, and finally school or district budget mone y. Rickels (2008) found significant positive correlations between marchi ng band budget and ratings ( r = .41, p < 01) as well as overall yearly band budget and ratings ( r = .46, p < 001). The mean marching band budget was reported as $7,768.65 with a sta ndard deviation of $12,421.89, and the mean overall band budget (for marching band, c oncert band, jazz band, and other activities combined) in this study was $14,516.28 with a standard deviation of $18,256.20. This extreme variability may indicate outliers of enormous budgets. For the marching band budget, the median value was $4,500 and th e inter-quartile range was $1,600 to $8,300, while the median value for the total band budget was $9,000 with an inter-quartile range
15 of $3,000 to $18,000. Considerable positive skewness was reported for both of these variables (although a specific number was not re ported). It is quite probable there would be one or more outliers in the data since any one of the approximately eighty bands involved in the research might have made a significant purchase during the year of data collection. Purchases that could cause an outlier might be one-time purchases or purchases which only occur once every several years such as a new set of uniforms, an equipment truck (some band programs own a semi tractor-trailer), or a large purchase of new instruments. The post-hoc Tukey test revealed significant differences between the budgets of bands receiving an overall Â“superiorÂ” rating ( n = 21, M = $16,092), an overall Â“excellentÂ” rating ( n = 41, M = $5,521), and an overall Â“goodÂ” or lower rating ( n = 15, M = $2,260). These numbers should be read with caution, however, because money is often spent in proportion to the number of students in the band, and as indicated by Davis (2000), Goodstein (1984, 1987), and Rickels himself, larger band sizes correlate positively with higher ratings. A smaller band will require less expenditure for equipment, repairs, transportation. It may have been helpful for RickelsÂ’ study to include the mean amount of mone y spent per student. One of the greatest single annual expe nses for a marching band can be the purchase of custom written drill and music. Hewitt (2000) correlated average marching band scores to different categ ories of show customization. He surveyed 439 high school band directors in ten states about how th eir show was written and gathered publicly available ratings to correlate with the gathered data. One major finding is that field drill custom-written for the band by somebody othe r than the director yielded significantly higher marching band scores than drill written totally or in part by the director. This
16 supports RickelsÂ’ (2008) findi ngs that greater budgets are correlated positively with higher ratings. One of the reasons for this may be that music educators may not be required to take a class in marching band me thods/drill design in order to earn their degree. Since drill design can be a very in tricate and complicated undertaking, especially with larger groups, the experi ence of a specialist in drill design who knows how to make a band sound and look good given their field positions and movements may result in a much more effectively designed show. The altern ative is for the director to write his or her own drill. This can save a great deal of money but requires a large time investment from the director who may be less experienced in drill writin g, has seen fewer bands on the field, and has observed them in a less critic al way than drill design specialists. One of the strengths of this study is that Hewitt broke down the categories of director involvement into three groups of i nvolvement Â– none, part, or all. Hewitt (2000) also found it was significantly more advantageous for directors to have all of their show music written for them rather than none, and approximately 32% of the variability in marching band ratings was due to the customized dr ill and show music. The justification for this is that custom-w ritten music is typically tailored to the individual strengths and w eaknesses of the given band, thus maximizing the bandÂ’s potential. This is often preferable over stock arrangements which are typically written for bands with average abilities in all sections of the band. A similar result wa s present in DavisÂ’ (2000) study where the use of custom wind and percussion parts showed a slightly positive (although non-significant) correlation with higher ratings. The addition of staff members such as percussion and auxiliary instructors can help the band director delegate responsibilities to people w ho specialize in a specific area
17 of music instruction. Quality staff members can be expensive to hire. Beaver (1973), Davis (2000), Jarrell (1971) Rickels (2008), Saul (1976) and Washington (2007) found there was a significant positive correlation be tween the number of instructors and ratings. The most frequently reported instructor was the auxiliary/color guard instructor and the second most common instructor was the percu ssion instructor. Other types of instructors include marching instructors, brass instru ctors, woodwind inst ructors, percussion instructors who work primarily with the front ensemble (sometimes called Â“pit percussionÂ”), and other music staff. Bands with multiple band directors (as opposed to instructors) earned Superiors more often than bands with a single director in DavisÂ’ study, but Rickels showed a non-significant low correlation ( r = .05) between number of directors and ratings. During marching band season there is a great deal of focu s on perfecting the music of the marching band show, which can result in students only working on the marching band show in class through the end of the season and not working on concert band music until after all marching activities ha ve ceased. Directors must decide whether to focus exclusively on the marching band s how or whether to budget time differently and work on concert band literature during class and relegate marching band music to after-school hours once band camp is comple ted. Rickels (2008) found a significant difference between the mean ratings of bands who only worked on the marching band show in class throughout the marching band season ( n = 39, M = 84.60) and those who worked on concert band music starting at the beginning of the school year ( n = 18, M = 88.77). Bands working exclusively on show mu sic in class may be victims of Â“overrehearsingÂ” which can dull student interest in the music resulting in less passionate
18 performances. Bands which actually need the en tire season to prepare their show music in class may be performing music which is above th eir ability level. There is great value to working on concert literature during marchi ng band season, such as reinforcing musical fundamentals, developing a greater focus on developing an appropr iate band sonority, and providing relief from the same eight mi nutes of show music being played every day for three months. Some music educators believe a band dire ctor is either good at marching band or good at concert band, but usually not both. Th is problem was investigated by Dawes (1989) and found there was no significant corr elation (positive or negative) between achievement in marching band and achievemen t in concert band. He also noted marching bands employing the one-show-per season model typically outperformed those learning multiple marching band shows in competition, but on average earned lower ratings in sight-reading at concert band festivals. Bands which rate higher generally attend more festivals. Rickels (2008) found a significant positive correlation ( r = .49) between number of fe stivals attended and ratings. While a band may get better as a result of reviewing and implementing the adjudicatorsÂ’ comments from a greater number of adjudica tors, it is also possible a reverse causal relationship may exist; bands which are quite successful attend more festivals to showcase their talents and receive commendati ons and recognition (B urnsed, Sochinski, & Hinkle, 1983; Fleming, 1975; Laib, 1984) Sheldon (1994) also found students who perceive music as being for a Â“competitiv eÂ” performance consider the music to be qualitatively better than for a non-adjudicat ed performance. Sullivan (2003) found that constructive input and exposure to other ba nds were seen as reasons to attend band
19 competitions, and inconsistent judging practi ces, funding inequities, and poorly organized festivals were found to be the most signifi cant drawbacks. There were significant differences in responses about the size of bands from schools of different sizes, although community density (rural, urban, etc.) did not result in a sign ificant difference. Factors not discussed above which correlated positively with band festival ratings for concert band included the use of a metr onome with rehearsal, the inclusion of noncontest music during regular rehearsals, and the use of outside music teachers rehearse or critique the band prior to the concert festiv al. Factors which influenced the success of marching bands included the use of an electr ic tuner and metronome, the use of outside music teachers to rehearse or critique the band prior to the festival, the bandÂ’s basic marching style, student participation in Â“spe cialtyÂ” camps (not supervised by the band director) for auxiliary, drum majors, and perc ussionists, and participation in half-time performances at school foot ball games (Washington, 2007). The Rating of Bands The aspect of consistency of scoring cr iteria in various national contests was examined by Oakley (1975). He requested judgeÂ’s sheets from 21 field show festivals and 16 parade band festivals to compare the crit eria used to evaluate the bands. Much inconsistency was found, alt hough the categories of music and marching were always present. General effect was the third categ ory considered and showed up on rating sheets in 18 cases. Many of the specific captions (e .g., tone, intonation, and balance) for bands were so highly related as to imply there may be a degree of overlap and that they are not fully independent. However, the final overall rating by each judge is considered to be a reliable indicator of performance achie vement (Burnsed, Hinkle, & King, 1985).
20 The methods employed by band director s during adjudicated sight-reading sessions at festivals was correlated to sight-r eading ratings and revealed the quantity and rapidity of instructi on resulted significant positive corr elations. Harris (1991) found the strongest positive relationships with sight-read ing ratings and the quantity of concurrent instructions (instructions gi ven while students were concu rrently performing a task) ( r = .481, p < .01), the quantity of expressive instru ctions (instructions relating to musical expression) ( r = .467, p < .01), the rate (speed) of concurrent instructions ( r = .423, p < .01), and the rate of non-c oncurrent instructions ( r = .419, p < .01). There was a single significant negative correlation between teaching techniques during si ght-reading and the sight-reading score, and that was the number of general instructions ( r = -.470, p < .01). This would imply that time during sight-read ing sessions is best spent talking about aspects of the music rather than logistical or procedural discussion (where to sit, which percussion players should play a given part and so forth). Bauer (1993) found varying the sight-reading routine is more effective than using the same procedure each time. Along with the importance of the criter ia on which a band is judged is how consistently these criteria are evaluated by the adjudicators. One of the premises music educators who participate in contests assume is that the judging is basically fair and that the system is valid. Guegold (1989) examin ed the Ohio Music Educators Association (OMEA) adjudication procedure to check fo r adjudicator consistency. He compared results from several bands attending OMEA stat e finals contest over a three year term to see if bands maintained consistent scores Although he found no compelling statistical results in the areas of cons istency, he did conclude ther e is a Â“reasonable chance for groups attending the OMEA State Finals to receive a fair evaluation in the form of
21 consistent rankings and ratingsÂ” (Guegold, 1989, p. 103). One of the weaknesses in this study is it assumes band quality doe s not vary significantly from year to year. He also did not take into account bands which may have changed directors, a potentially significant confounding variable. Synthesis of Band Ratings The preceding studies suggest larger school s, larger bands, and larger budgets correlate positively with higher ratings. The literature on factors affecting band ratings reveals a number of importan t things. Beaver (1973), Dawes (1989), Davis (2000), Fosse (1965), Goodstein (1984), Maxwell (1970), Mann (1979), Saul (1976), and Washington (2007) found positive correlations between band ratings and the academic degree and years of teaching experience of band directors. Factors outside the immediate control of the band director which correlated positively with band ratings included larger school size and larger band size (Beaver, 1973; Caimi, 1981; Davis, 2000; Fosse ,1965; Goodstein, 1984 & 1987; Rickels, 2008; Saul 1976), having a higher percentage of juniors and seniors in the band (Harris, 1991; Washington, 2007), larger budgets and greater ability to raise funds (Goodste in, 1984; Goodstein, 1987; Rickels, 2008; Washington, 2007), having a highly customized marching band show, including drill and music (Hewitt, 2000), having larger numbers of assistant director s and staff members (Beaver, 1973; Davis, 2000; Jarrell, 1971; Rickels, 2008; Saul, 1976; Washington, 2007), and attending a larger number of festivals and competitions. It is important to note here that many of these non-director related factors are essentially financial, which reinforces the positive correlations betw een large budgets and bands receiving high ratings. Another noteworthy factor which correlates positively with higher band ratings includes when a
22 band director begins rehearsi ng concert band literature earlie r in the school year rather than waiting until after marching activi ties are concluded (Rickels, 2008). Personality and Music Educators The study of personality and its classifi cation has a long history dating back more than two thousand years, including one of the earliest known persona lity classification systems of the four temperaments: sangui ne, phlegmatic, choleric, and melancholic developed by Hippocrates (Kemp, 1996). Sin ce then, many psychologists have developed the field of understanding and classifying pers onality types and traits. One of the most common personality inventories is the MyersBriggs Type Indicator (MBTI), which was developed from the theories of Carl Jung in 1958 (Keirsey & Bates, 1984; Tyler, 1954). This model classifies personalities through f our bi-polar dimensions: Introvert/Extrovert, Sensing/Intuitive, Thinking/Feeling, and J udging/Perceiving. Personality types are indicated as a set of four le tters, representing the first le tter of each personality type, except for the Intuitive type which is represen ted by the letter N. This inventory attempts to describe personality types while some other personality in ventories attempt to describe personality traits The sections which follow includ e discussion of the personality profiles of music educators and implications of the four Myers-Briggs dimensions in music educators. Developing the Myers-Briggs dimens ions further, Keirsey established temperaments based on the sixteen personality types attainable th rough the MBTI. Each type was given a label which represented t ypes of professions or vocations. There are four primary temperaments, which are Idealist Rational, Guardian, and Artisan. Each of these four temperaments can be further broken down with the addition of another
23 dimension of personality. Idealists may be Me ntors or Advocates while Rationals may be Coordinators or Engineers. Guardians may be Administrators or Conservators while Artisans may be Operators or Entertainers. The final dimension of Extraversion/Introversion dete rmines the sixteen personality types (Keirsey & Bates, 1984). Figure 1 displays how the temperaments are organized and how the Myers-Briggs personality types represent these temperam ents. From the perspective of a music educator, it should be noted that the Teacher pe rsonality (ENFJ) shares very little with Performer (ESFP), and is the polar opposite of Composer (ISFP). This is something that should be considered carefully when examini ng the personality of music educators, who are teachers by profession but often start as student performers or composers. Temperament Role Role Variant Abstract vs. Concrete Cooperative vs. Utilitarian Directive vs. Informative Expressive vs. Reserved Introspective (N) Idealist (NF) Diplomatic Mentor (NFJ) Developing Teacher (ENFJ): Educating Counselor (INFJ): Guiding Advocate (NFP) Mediating Champion (ENFP): Motivating Healer (INFP): Conciliating Rational (NT) Strategic Coordinator (NTJ) Arranging Field Marshal (ENTJ): Mobilizing Mastermind (INTJ): Entailing Engineer (NTP) Constructing Inventor (ENTP): Devising Architect (INTP): Designing Observant (S) Guardian (SJ) Logistical Administrator (STJ) Regulating Supervisor (ESTJ): Enforcing Inspector (ISTJ): Certifying Conservator (SFJ) Supporting Provider (ESFJ): Supplying Protector (ISFJ): Securing Artisan (SP) Tactical Operator (STP) Expediting Promoter (ESTP): Persuading Crafter (ISTP): Instrumenting Entertainer (SFP) Improvising Performer (ESFP): Demonstrating Composer (ISFP): Synthesizing Figure 1. KeirseyÂ’s Temperaments with Myers-Br iggs Personality Types, adapted from Keirsey and Bates (1984).
24 Cattell developed a personality trait inventory known as the Sixteen Personality Factor Questionnaire These sixteen factors are denoted by letters indicating the factor itself followed by a plus or mi nus which places the subject into one of the bi-polar categories. CattellÂ’s firs t-order factors are Aloofne ss (A-)/Outgoingness (A+), Low Intelligence (B-)/High Intelligence (B+), Lo w Ego Strength (C-)/Hi gh Ego Strength (C+), Phlegmatic (D-)/Excitability (D+), Submissi veness (E-)/Dominance (E+), Desurgency (F-)/Surgency (F+), Expediency (G-)/Conscientiousness (G+), Shyness (H+)/Adventurousness (H-), Tough-Mindedne ss (I-)/Sensitivity (I+), Zestful (J)/Individualistic (J+), Trusting (L-)/Suspici ous (L+), Practical (M -)/Imaginative (M+), Naivet (N-)/Shrewdness (N+) Self-Assured (O-)/Guilt Pr oneness (O+), Conservatism (Q1-)/Radicalism (Q1+), Group Dependent (Q 2-)/Self-Sufficiency (Q2+), Low SelfSentiment (Q3-)/High Self-Sentiment (Q3+), and Low Ergic Tension (Q4-)/High Ergic Tension (Q4+) (Cattell & Schuerger, 2003; Kemp, 1996). Since the 1980s there has been an increasing amount of agreement among personality researchers and psychologists that the most parsimonious model of personality typing is composed of five ba sic dimensions. Eventually, the Five-Factor Model made up of the dimensions Openness to Experiences (Â“OÂ”), Conscientiousness (Â“CÂ”), Extraversion (Â“EÂ”), Agreeableness (Â“ AÂ”), and Neuroticism (Â“NÂ”) emerged through a degree of consensus among personality res earchers, which are considered to be independent higher-order pers onality factors (M cCrae & Costa, 2003; Piedmont, 1998). Another major development with this Five-F actor Model is it describes subjects by the degree to which each of those five factors are present along a continuum rather than being forced into a polarized category. Th is model has been employed in psychological
25 counseling and job selection si nce shortly after its inception, but later Costa and McCrae presented it as a possible t ool in clinical psychopathol ogy as well (McCrae & Costa, 2003; Piedmont, 1998; Schinka, Kinder, & Kr emer, 1997). This Five-Factor Model has become the dominant model for the invest igation of personality (Piedmont, 1998; Young & Schinka, 2001). Each of the five categories includes six s ubsidiary factors, or Â“facets.Â” The facets for Openness are fantasy, aesthetics, feelings actions, ideas, and values, the facets for Conscientiousness are competence, order, dutifulness, achievement striving, selfdiscipline, and deliberation, the facets for Extraversion are warmth, gregariousness, assertiveness, activity, excitement seeki ng, and positive emotions, the facets for Agreeableness are trust, straightforwardness, altruism, compliance, modesty, and tendermindedness, and the facets for Neuroticism are anxiety, angry hostil ity, depression, selfconsciousness, impulsiveness, and vulner ability (See Figure 2) (Kemp, 1996). The inventory developed by Cost a and McCrae in 1992 w is known as the Neuroticism Extraversion Openness Personality Inventory Revised, or NEO-PI-R (McCrae & Costa, Dimensions Openness to Experience Conscientiousness Extraversion Agreeableness Neuroticism Facets Imagination Self efficacy Friendliness Trust Anxiety Artistic Interests Orderliness Gregariousness Morality Anger Emotionality Dutifulness Assertiveness Altruism Depression Adventurousness Achievement Striving Activity Level Cooperation Self Consciousness Intellect Self Discipline Excitement Seeking Modesty Immoderation Liberalism Cautiousness Cheerfulness Sympathy Vulnerability Figure 2. The Five Factor Model of Personality: Dimensions and Facets. Adapted from Kemp (1996).
26 2003; Piedmont, 1998), although adaptations of the Five-Factor Model have been developed by a number of psyc hological researchers as well. Test items for a five-factor personality inventory have been gathered and organized into computer-based public domain pool of items known as the Intern ational Personality It em Pool, or IPIP (Goldberg, 1999). Education research reveals that a teache rÂ’s personality can influence his or her teaching, classroom behavior, and education goals (Job, 2004). Zhang (2007) found teacher personality, as measured by the Five-F actor Model, significantly contributed to a teacherÂ’s teaching style, more than gender, education level, and quality of students. A study which examined teacher personalit y in the Five-Factor Model revealed Conscientiousness did not relate significan tly to occupational success. Assertiveness, which is a facet of Extraversion, indicated mo re meaningful relati onships with teaching quality than Extraversion, and Envy-Jealousy, a facet of Neuroticism, tended to enhance teaching quality more than Neuroticism (Emmerich, Rock, & Trapani, 2006). Different results for the Conscientiousness factor we re found by Chamorro-Premuzic, Furnham, and Lewis (2006) where it was associated with Â“deep and achieving learningÂ” approaches (based on BiggsÂ’ model of study processes). Deep learning was also associated with Agreeableness and Openness to Experience, a nd was negatively correlated with BiggsÂ’ Â“surfaceÂ” approach to learning. Job (2004) f ound similar positive results for high levels of Conscientiousness, which was positively co rrelated with teaching effectiveness along with high levels of Extraversion a nd low levels of Neuroticism. Education research which focused on the Myers-Briggs Type Indicator showed significant correlations between personality types and teaching efficacy. In a study
27 focusing on the teaching efficacy of agriculture teachers, Extraversion was significantly positively related to teacher efficacy, Judgi ng was positively related to classroom management, and Sensing was significantly ne gatively related to student engagement (Roberts, Harlin, & Briers, 2007) Teachers in Florida have be en considered in light of their MBTI types, revealing that the traditionalists tende d to be Sensing and Judging, while more Intuitive and Perceptive type s were recommended as being necessary to increase innovation and visions for new m odels of education. The ENFP type was identified as the most likely personality to be educational leaders in Florida, and many recipients of FloridaÂ’s Teacher of the Year award were of this personality type (Rushton, Morgan, & Richard, 2007). Personality research in music educati on has predominantly employed the MyersBriggs Type Indicator. However, the Five-Fac tor model of personality incorporated in the NEO-PI-R of Costa and McCrae has been consid ered to be a more modern and effective tool for analyzing personality (Kemp, 1996) due to its non-polarized dimensions. A subjectÂ’s personality with the MBTI must be la beled as either Introvert or Extravert, even if they are closely split betw een the two types. The benefit of the NEO-PI-R is that a subject is simply indicated as to their degr ee of Openness or Conscientiousness, rather than being categorized as wholly one t ype or another (Goldberg, 1999; Johnson, 2005). Costa and McCrae also include thirty sub-categor ies (six for each of the five dimensions) called Â“facetsÂ” which may isolate specific pers onality factors as being related to teaching style or achievement at band festivals. The body of personality research in musi c education cannot always be safely generalized to practicing music educators, as in many cases th e subjects of this research
28 were music education students (Kemp, 1996; Lanning, 1990; McCutcheon, Phillips, 1997; Schmidt, & Bolden, 1991; Steele & Young, 2006; Venesile, 1992; Wubbenhorst, 1994). The subjects of those studies which do focus on active professi onal teachers were usually college-level applied music te achers (Donovan, 1994; Fedor uk, 1992; Kim, 1993; Lewis, 1998; Schmidt, 1989). Notable exceptions are the research of Bullock (1974), Stitt (1997), Stuber (1997), and We stbrook (2004) who did study middle and high school band directorsÂ’ personalities. The personality of music educators is not the only factor which influences success in music programs. Student personalities ha ve been found to affect dropout rates in instrumental music programs. Mowery ( 1993), using the MBTI, found Intuitive students in a string orchestra program were much more likely to remain in the group than Sensing students, which was the personality type of most orchestra dropouts. The SensingIntuition mode was the only dimension to co rrelate significantly w ith dropout rates. Other personality and professional inventorie s have been incorporated in research in music as well. When examining the relatio nship between student teacher effectiveness and occupational personality types (Realistic, I nvestigative, Artistic, Social, Enterprising, and Conventional), Teachout ( 2001) found none of these type s contributed significantly to the variance of teaching effectiveness. Howe ver, the three highest mean scores were in the Artistic, Social, and Investigative categories. Personality Profiles of Music Educators To develop an understanding of how persona lity plays a role in music education, an important first step is to examine some of the most prevalent personality types in existing research. Several studies have descri bed typical personalities of music educators
29 or music education students in various fields of specialization. So me of these studies begin to describe what might be considered typical or even ideal personalities in these fields. Earlier research on music educators i ndicated a preponderance of CattellÂ’s factors of dominance (E+), adventurousne ss (H+) and self-sufficiency (Q2+), but also lack of imagination (M-) and trustingness (L-), but also that they were more warmhearted, conservative, and group-dependent than mu sicians (Kemp, 1996). Wubbenhorst (1994) and Kemp (1979) both found music education st udents tended to be evenly split between Extraversion and Introversion, showed a slig ht preference for Intu ition, and showed a preference for Judging. Wubbenhorst found an ev en distribution on the Thinking/Feeling dimension, while Kemp found a very strong pr eference for Feeling (84%). Wubbenhorst and Kemp found different results for music pe rformance students in the dimensions of Extraversion/Introversion and Judging/Per ceiving, even though in both cases the differences were rather slight They found musicians were mo re Intuitive (66% in both studies) and Feeling (57% in Wubbenhorst 1994; 74% in Kemp, 1996) than music education students. A study comparing the personali ties of elementary and secondary music education students revealed significantly different personalities. Elementary music education students had a tendency to be more Extraver ted (80%), Sensing (74%), Feeling (80%), and Judgmental (85%), resulting in a very strong tendency towards an ESFJ (KeirseyÂ’s Â“ProviderÂ” temperament) personality. Seconda ry music education students were more often Introverted (61% ), Intuitive (54%), Thinking (57%), and Perceiving (54%) resulting in an INTP (Â“Archite ctÂ”) personality which is less consistent than that of elementary music teachers (McCutcheon, Sc hmidt, & Bolden, 1991). The traits of
30 secondary music education students are much mo re similar to the typical INFP (Â“HealerÂ”) personality of performing musicians as de termined by both Kemp and Wubbenhorst. This seems to be an important distinction to take into consideration when looking at the results of personality assessments for music educator s. Without separate results for different career tracks, meaningful correla tions may be difficult to find. Contrary to the findings of McCutcheon, Schmidt, and Bolden (1991), both Stitt (1997) and Westbrook (2004) found high school band directors showed strong tendencies toward Introverted, Sensing, Thinking, and Judging personalities (ISTJ, Â“InspectorÂ”), although the Introversion/Extraversion dimension was nearly balanced in StittÂ’s study. It is important to note that while McCutcheon, Schmidt, and Bolden examined music education students, Stitt and Westbrook examined the persona lities of active band directors. Steele and Young (2006) found the most common personality type of music education students from eleven different U.S. universities to be ENFP, although the Judging/Perceiving trait was split at 49.7%/50.3% respectively, a very small difference. A study of seven applied studio instructors re sulted in a typical personality of INFJ (Â“CounselorÂ”), which is also similar to performing musicians (Donovan, 1994). Gender does not seem to play as large a role in dete rmining personality types in music educators. The majority of males were ENFP (Â“Champi onÂ”) while females were predominantly ENFJ (Â“TeacherÂ”) in a survey of music educ ation majors at seven Oklahoma universities (Lanning, 1990). Ethnicity may affect person ality tendencies, as 145 music and music education majorsÂ’ personalities at six histor ically African-American universities differed from many of the personality types found above. The sample resulted in several personality types by gender, major (music education or performance), and applied
31 instrument/voice. The majority of males were ISTJ (Â“InspectorÂ”) and females were ESTJ (Â“SupervisorÂ”). Brass majors were ESTJ, and keyboard majors were ISTJ. Voice majors were ESJ with an even distribution of Th inking and Feeling, woodwind majors were STJ with Extraversion and Introversion evenly di stributed, and percussion majors were IST with an even distribution of Judging and Per ceiving. Music Education majors were ESTJ (Â“SupervisorÂ”), while Music majors were pr edominantly ISTJ (Â“InspectorÂ”) (Phillips, 1997). The main difference between this sample and other findings is the preponderance of Sensing and Thinking types, where many ot her findings indicated Intuitive and Feeling types were more common. The one significant similarity is that the Sensing/Thinking music education students in Ph illipsÂ’ study were very similar to active band directors in StittÂ’s (1997) and WestbrookÂ’s (2004) study. It is not necessary that student and t eacher personalities match in order for students to feel satisfied. Kim (1993) found there was no significant correlation between match of student to teacher personality and student satisfaction. She also found Extraverted (E), Thinking (T), and Judging (J ) types shared similar teaching styles, and Introverted (I), Feeling (F), and Perceiving (P) types also sh ared similar teaching styles. A teacher may adopt teaching styles which they feel compensate for weaknesses in their personality traits. Fedoruk (1992) looked at the pers onality and teaching style of six collegiate voice studio teachers to determine what relations existed between teaching style and personality. The pers onality type was determined using the Myers-Briggs Type Indicator (MBTI) and teaching st yles were described qualita tively. Some observations include that the MBTI was helpful in desc ribing the teaching styles, but the teacherÂ’s MBTI type was not a good predictor of t eaching style, and teachers can learn to
32 incorporate teaching styles which are not typi cal of their personality type (an Intuitive using Sensing modalities in teaching). Implications of Myer s-Briggs Dimensions in Music Educators A number of research studies were conducted, mostly in the 1990s, which examined the effect of the various dimensi ons of the Myers-Briggs Type Indicator on aspects of music education. So me of these aspect s include teaching behaviors, teaching effectiveness, student achievement, and pr ofessional achievement. These findings are organized by each of the MBTI dimensions and discussed below. The Introversion/Extraversion Dimension. Perhaps the greatest number of significant findings as well as the greatest number of seemingly contradictory fi ndings pertains to the Introv ersion/Extraversion dimension. Interestingly, those findings which point more favorably towards Extraverted personalities focus on private applied teacher s, often at colleges and universities. Those studies which found more positive evidence fo r Introverted teachers largely featured classroom music educators as their subject s, especially middle and high school band directors. Some studies found favorable results for Extraverted subj ects. In a group of fortyfive private applied teachers the Extraverted teachers di splayed a significantly higher degree of approving behavior during lessons than the Introverted teachers (Schmidt, 1989), and students made more progress in their applied lessons with Extraverted teachers than with Introverted teachers (Donovan, 1994). In a group of college piano teachers, students indicated a higher satisfac tion with Extraverted teachers, who favored nonverbal teaching styles, group instruction, and an analytical approach more than the
33 Introverted teachers (Kim, 1993). Extraverted music educators tended to take student interests into consideration when teaching, wh ile Introverts tended to be overly familiar with their students (Kemp, 1996). Extraverted el ementary music education students spoke to students with an expressive vo ice in class (Venesile, 1992). Another group of researchers found more positive results for educators with an Introverted personality. Introvert ed music educators were more receptive to supervisorsÂ’ criticism and were more willing to adjust th eir teaching to improve than Extraverts, who readily give feedback to stude nts but who are themselves resi stant to feedback from their own supervisors (Kemp, 1996). Introverted co llegiate piano instructors were more verbally oriented, preferred individual instruction, emphasized functional skills, and tended to employ more holistic or global teaching styles (Kim, 1993). Introverted personalities correlated positively with teaching success in fourteen former students of a famous applied violin instructor, while Ex traversion correlated ne gatively (Lewis, 1998). Students rated their band directors with Introverted types hi gher on the Director Evaluation Scale (DES) items Â“Brings out the best in students,Â” Â“DoesnÂ’t talk down to students,Â” along with the total DES score, th e dimension of musicality, and showed the highest percentage of positive non-verbal be havior (Stitt, 1997). In a study where the subjects were a group of twenty band dire ctors, 70% of the directors in the more experienced group were Introverted while 70% of less experienced directors were Extraverted. Although with such a small sample this may be due to chance, it may also indicate Extraverted band dire ctors are less likely to rema in in the profession for longer periods of time. Introverted band directors spent more time on warm-ups and tuning than Extraverted types, preferred concrete lear ning styles and were more approving in
34 teaching situations while Extraverted teacher s more often preferred abstract learning styles and were more ofte n disapproving (Stuber, 1997). The research here supports Introversion as a more effective personality trait for high school band directors. A lthough there are some studies which show more positive results from Extraverted teachers, the subjec ts of these studies are primarily applied music instructors at the college or university level, or music education students. This is also reinforced by the findings of McCutcheon, Schmidt, and Bolden (1991) in that music education students focusing on secondary sc hools were more Introverted, especially when compared to elementary music education majors. The Sensing/Intuitive Dimension. As noted earlier, many studies have show n Intuition to be a common personality type in musicians and music educators. Fi ve out of six applied music teachers had Intuitive rather than Sensing personalities in FedorukÂ’s (199 2) study, which is consistent with KempÂ’s (1996) findings about music educators. In mo st of the studies where the Sensing/Intuitive dimension provided notable results, the results favored Intuitive types. Intuitive teachers provided significantly more modeling, more approval feedback to students, had a higher rate of reinforcemen t, and maintained a more rapid pace during lessons (Schmidt, 1989). Rhythmic sense and a ccuracy was scored highest with Intuitive teachers who taught Sensing students (Donovan, 1994). One study found favorable results for Sensing types, where Sensing band directors were rated by students as being more empathetic and better at communicati on than Intuitive directors. Notwithstanding, Intuitive directors also had a positive finding in the same study: they used more positive verbal behavior (Stitt, 1997).
35 The Thinking/Feeling Dimension. Relatively few studies found significant resu lts pertaining to the Thinking/Feeling dimension, especially compared to the Introv erted/Extraverted dime nsion. Those that did produced more favorable findings for Thinki ng types, although there were also some positive findings for Feeling personalities. A group of private applied piano students indicated a higher satisfaction with teachers of Thinking personality types more than the Feeling teachers. These Thinking types favored nonverbal teaching styles, group instruction, and an analytical approach (Kim, 1993). Thinking band directors spent more time on warm-ups and tuning than Feeling types, who were more often disapprov ing, spent more time in breaks, and spent more time disciplining students than Thinki ng types (Stuber, 1997). Directors with the Thinking personality were considered to be mo re empathetic than Feeling directors (Stitt, 1997). Some aspects of Feeling types include being perceived by students as more musical and more effective at communication than Thinking directors (Stitt, 1997), and that Feeling personality types were more verbally oriented, preferred individual instruction, and tended to em ploy more holistic or global teaching styles (Kim, 1993). Rhythmic sense and accuracy was scored highest for Feeling teachers who taught Thinking students (Donovan, 1994). The Judging/Perceiving Dimension. Neither pole of the Judging/Perceivi ng dimension dominates as a common personality type among musicians or music e ducators, although the literature suggests Judging types are more desirable for educator s. Judging type band directors showed more
36 empathy and effective communication skills than Perceiving directors who were considered more overbearing (Stitt, 1997). Judging types were better able to give students more information during class, although the more hesitant Perceiving types were more flexible with their teaching and could accommodate student interests (Kemp, 1996). Elementary music education students of th e Judging type stimulat ed student interest, showed confidence, used time effectively, and used instruments, body movement, and singing in a musical way (Venesile, 1992) The Judging personality types favored nonverbal teaching styles, group instruction, and an analytical approach. Students indicated a higher satisfacti on with Judging teachers than Perceiving teachers (Kim, 1993). Applied instructors with a combinati on of Extraversion and Judging had the highest mean rate of reinforcement, approval, and pace (Schmidt, 1989). The only findings on Perceiving personality types were that they were more verbally oriented, preferred individual inst ruction, focused on affective aspect s of musicianship, and tended to employ more holistic or gl obal teaching styles (Kim, 1993). Personality Synthesis The literature indicates some of the mo st common Myers-Briggs personality types for music and music education students and professionals include Intuitive types and Feeling types. The literature also indicates there is a rela tively even distribution of Introverts and Extraverts, as well as Judge rs and Perceivers. Studies which focus primarily on band directors i ndicate the highest percentage of personalities are ISTJ (Inspector). Despite these being the most common types, the literature does not necessarily consider them the most profe ssionally advantageous. The studies mentioned
37 above indicate the most effective personali ty for a high school band director may be Introverted, Intuitive, Thinking, and Judging, or INTJ (Mastermind). Music Educators and Teaching Style The term Â“teaching styleÂ” refers to the wa y in which a person balances his or her teaching responsibilities and what level of prio rity he or she assigns to these aspects of the profession. Teachers do many different things during their time with students such as rehearse music, teach musical concepts, demons trate, play recordings, lead or facilitate discussions, and so forth. Other duties incl ude administrative res ponsibilities such as taking attendance, disciplining students, reading announcements, managing fire or tornado drills, and collecting forms or money. In an ideal situation, the entire class period might be spent engaged in musical teaching and learning activities. In reality, this is seldom the case. Blocher, Greenwood, and Shellahammer (1997) found that a group of Florida band directors spent an average of approximately 9% of class time performing non-musical activities such as administra tive tasks and disciplinary procedures, approximately 8% giving feedback to stude nts, 49% conducting and listening to students nonverbally, 31% giving verbal directions, a nd approximately 3% delivering conceptual information to students. This is reinforced with GoolsbyÂ’s studies on the effectiveness of time use of student teachers, novice teacher s, and experienced teachers who regress slightly from being a constantly mentored student teacher to novi ce, but then improve significantly in how they use rehearsal time as they become experienced teachers (Goolsby 1996, 1997). The published literature on music teaching styles falls into three main topic areas which are discussed below. These are teaching style and its effect on ensemble ratings,
38 GummÂ’s model of teaching styl e, and other models of music teaching style which have been considered. Teaching Style and Ratings Some research has shown the teaching st yles and behaviors of music educators may influence ensemble performance quality. Smith (1999) examined the teaching styles of four band directors in an in-depth qualitative study for types of verbal and nonverbal communication and how they correlated w ith marching band ratings. Higher contest ratings were positively correlated with speaki ng about notation, rhythm, and style. Bauer (1993) found higher ratings were positively correlated with working on balance and intonation and a consistent ut ilization of a rhythm counti ng system. Directors talking about expression and rhythm were found to corr elate with higher ratings than directors talking about general matters, notation, or stylistic aspects of the music. Higher ratings were correlated with direct indication of a pproval or disapproval than general comments of approval or disapproval to the group as a whole. This relates to the educational ideal that specific praise is better than general praise. Verbal imagery and questioning actually showed a negative correlati on with higher contest ratings although demonstration and modeling showed a significan t positive correlation. The way in which teachers manage their classrooms is an important aspect of teaching style. In a survey of choir dir ectors in Michigan, Costello (2005) found high levels of self-reported classroom management sk ills as well as high levels of self-reported satisfaction with school dist rictÂ’s professional developm ent opportunities pertaining to classroom management skill development had significant positive correlations with ensemble ratings at festivals ( r = .45, p = .02, and r = .42, p = .03, respectively). Price
39 (1983) and Yarbrough and Madsen (1998) found si milar results in that the directors who had the highest rated performances conducted reh earsals with the least off task behavior, the most teacher eye contact, more changes of activity, and the av erage length of any activity by student or teacher was approxima tely five to six seconds. Yarbrough and Madsen also found that directors who rehear sed shorter sections of the music during rehearsals were consistently rated as higher in overall performance quality than those who typically rehearsed longer sections. Some teaching behaviors that relate to student achievement include verbal instruction and teacher assistance during prac tice. During an examination of two schoolsÂ’ rehearsal seasons leading up to adjudicated performances (for a total of 83 rehearsals), Davis (1998) found both instructions and t eacher assistance during student practice decrease with student improve ment. One factor which greatl y affects the generalizability of this study is that there are only two di rectors involved in th is case study. It is noteworthy that more than forty rehearsals were observed with each director, although the small number of subjects does create a pr oblem for generalizing the results to other situations. GummÂ’s Model of Teaching Style The phrase Â“teaching styleÂ” is not new to the teaching profession, although its specific meaning has often been subjectiv e, imprecise, or even vague. Alan Gumm (2003a) examined the subject of teaching styles in depth and created a structured system of classifying and categorizing the teaching st yles of music educators. In this system, teaching style is not determined by individua l behaviors in the classroom, but rather it considers the underlying philosophy and motiv ation for these sets of behaviors.
40 Specifically, Â“The primary explanation behind the nature of music teaching style is that it is based on an individualÂ’s principles Â” (italics original) (Gumm, 2003a, p. 13). He proposed a three-level model consisting of teaching behavi ors, dimensions of music teaching style, and music teaching style itse lf. There are eight dimensions: Assertive Teaching, Nonverbal Motivation, Time Effici ency, Positive Learning Environment, Group Dynamics, Music Concept Learning, Arti stic Music Performance, and Student Independence. Gumm created a Â“Music Teachin g Style InventoryÂ”, or MTSI which is a set of questions which help teachers identify their teaching priorities. Teachers may have higher or lower scores on each of the ei ght dimensions, but should not categorize themselves under discreet labels by these di mensions. Instead, the teacher should develop an understanding of strengths and weaknesses based on the results. In one application of the MTSI, Gumm examined the correlation be tween choir directorsÂ’ music teaching style and festival ratings and found teachers whos e ensembles received higher ratings focused more on Artistic Music Performance a nd Nonverbal Motivation (Gumm, 2003b). GummÂ’s teaching styles include four dimensions that ar e classified as primarily teacher-directed (Assertive Teaching, Nonverb al Motivation, Time E fficiency, Positive Learning Environment) and four dimensions that are classified as primarily studentdirected (Group Dynamics, Music Concept Learning, Artistic Music Performance, and Student Independence). Bazan (2007) surv eyed middle school band directors in Northeastern Ohio for their predisposition to be student-directed or teacher-directed in their teaching styles and found teacher-directe d styles were more prevalent. The mean ratings revealed a mean of 4.00 (frequently) on a 5-point Likert-type scale for teacherdirected styles and a mean of 3.08 (sometimes ) for student-directed styles. Results were
41 compared between males and females, although it could not be determined whether gender differences impact teaching styles Generally, younger teachers were found to employ student-directed teaching styles more th an older teachers. This may be a result of the younger teachers recently coming from teacher education programs in which more modern student-directed peda gogy strategies were part of the curriculum. This is supported by Kelly (1972), Hamann (1990) Spurlock (2002), and Webb and Baird (1968) who found that student-centered classr oom environments also contributed to higher levels of student achievement. T eachout (1997) found similar results when comparing the opinions of experienced and preservice music teachers on the importance of forty different teaching skills. The pres ervice music teachers ranked maintaining student behavior and maximizing time on task much lower than experienced music teachers, which may imply a lower priority for GummÂ’s teacher-directed dimensions. This might be a result of a different attitude towards teaching or possibly from a lack of awareness of what is truly necessary to ma intain an orderly and effective classroom. Bazan also found schools with hi gher standardized test scores had a significant negative correlation with attention to student independence and student self-res ponsibility. This may be a result of a fact-driven scholastic atmosphere or attitude fostered by the administration to garner the highest sc ores on these standardized tests. Some teaching styles may work well with some students and less well with others. Brakel (1997) considered the possibility that teaching style predicts attrition in band programs by investigating and correlating dr opout rates with the ten teaching styles present in one of GummÂ’s earlier versions of the MTSI. Indivi dually, no teaching style predicted band attrition as there were no signi ficant correlations be tween any individual
42 teaching style and dropout rates. However, cer tain pairs of teaching styles did correlate significantly with dropout rates. High dropout rates had significant positive correlations with the combinations of Student Indepe ndence with Aesthetic Music Performance, Aesthetic Music Performance with Musi c Concept Learning, Aesthetic Music Performance with Eye Contact, Modeling with Positive Learning Environment, Teacher Authority with Eye Contact, and Positive Lear ning Environment with Eye Contact. These pairs may indicate a more traditional teaching style than the low-dropout pairs as the pairings seem to point to low degrees of student autonomy and greater teacher control. Low dropout rates had significant positive correl ations with the combinations of Student Independence with Positive Learning Environm ent, Student Independence with Critical Evaluation, Aesthetic Music Performance w ith Nonverbal Motivation, Modeling with Student Led Rehearsal, Modeling with Cri tical Evaluation, Verbal with Eye Contact, Verbal with Student-Led Rehearsals, and Ey e Contact with Critical Evaluation. These pairs which predict low dropout rates are largely student-o riented and indicate greater degrees of student freedom, intellectual indepe ndence, and ability for students to express themselves. Liberman (1986) found similar re sults with students in a non-music based educational setting. Other Models of Music Teaching Zhukov (2004) created a teaching and lear ning style classification system for private instrumental instructors in conserva tories in Australia. Fi ve different teaching styles were classified as disorganized positive, routine, imposing, and extrovert. Disorganized teachers led lessons which lack ed organization and direction, and included a large amount of talking on non-musical matters. Positive teachers employed teaching
43 strategies which are generally considered e ffective teaching such as positive specific feedback and specific questioning techniques. The largest group of teachers fell into the Routine teaching style, in which lessons we re structured although less inspiring. There was a preponderance of genera l directions and little teac her demonstration. The secondlargest group of teachers was labeled as Imposing, where the teachers dominated the lessons. These lessons contained high levels of technique and teacher demonstration, but low levels of positive specific feedback or specific questioning were included. The final teaching style was labeled Extrovert. The mo st prevalent behaviors included teacher demonstration, positive global feedback, and positive specific feedb ack, but less time was spent on general directions and giving answers to students. Effective teachers adjust their teaching st yle to suit the learning style of their students. College students po ssess different stages of l earning development just as younger students do, and it is important for prof essors at the college level to understand these developmental stages so they can adjust their teaching styles to best help their students. Cutietta (1990) examined three ma jor stages of development for college students: dualism, multiplicity, and relativism, and then proposed effective ways to best reach these learners. Dualism is typically experienced by high school students and college freshman. Students perceive a polar ized world of right or wrong, and the professors are authority figures who are expected to dispense the truth. With these types of students, the best approaches include lectures and demonstrations. When students reach the end of their first year and beginni ng of their second year, they often begin to conceive of the world through a broader pers pective, and there can be multiple truths. This developmental stage is known as multiplicit y. In this stage, all truths are equal,
44 everybody has a right to an opinion and thos e opinions are all equally valid, and the concept of better or worse begins to disappear In this stage students can start to believe they know as much as their professors. For this reason, this is the stage where most college drop-outs occur. To address these st udentsÂ’ needs, effectiv e teaching strategies include students developing their own crea tivity through creative assignments, small group discussions, and reaction reports to assi gned readings. The third and final stage is relativism, where students start to realize if al l things truly are equal, then there can be no basis to make a decision. Students who are posed with the questi on, Â“What styles of music would you include in your classroom?Â” are forced to confront the fact that they must use their own judgment and values to wo rk past a state of pure multiplicity in order to function as a professional. Teaching styles that are effective with these types of learners include seminar, individual presentations a nd research, and small group discussions. Teaching Style Synthesis The literature on teaching style does indi cate that it can influence ensemble performance outcomes (Costello, 2005; Davis, 1998; Gumm, 2003b; Gumm, 2004a; Yarbrough, 1998), although the term Â“teaching styleÂ” has not always meant the same thing. GummÂ’s model consisting of eight differe nt teaching styles has helped to better understand which teaching styles may influen ce behavior and performance outcomes, and helped educators understand which styles they employ and to what degree. The research indicates the four student-direc ted teaching styles are less prev alent than the four teacherdirected styles but may be indicators of more effective teaching (Bazan, 2007; Brakel, 1997; Gumm, 1993; Gumm, 2003a; Gumm, 2003b; Gu mm, 2004a; Gumm, 2004b;
45 Gumm, 2007). Other studies which examined music teaching style but not applying directly to K-12 music educators include Cu tiettaÂ’s (1990) th ree-level classification of teaching styles as they apply to college students and ZhukovÂ’s (2004) research on the teaching styles of applied music teachers in Australia which resulted in a five-category classification system of teaching style. Synthesis of Literature and Conclusions The three fields of research included in the literature review seem to reveal important information as well as gaps in the knowledge. The research on factors influencing band ratings indica tes a number of correlating f actors, many of which have financial investment as their foundation. Di rector factors such as education and experience have been researched, but the pers onality and teaching style of the director have not been directly examined as possi ble factors influencing band ratings. The literature on music educator personalities is expansive a nd indicates common personality types but only includes a small number of studies which focus on band directors and how their personality types may affect their band Â’s performance achievement. The majority of the literature also incorp orates the Myers-Briggs T ype Indicator, which many psychologists and personality researchers ha ve replaced with Cost a & McCraeÂ’s fivefactor model as the personality type indi cator of choice. The body of teaching style research reveals important knowledge on how teaching styles affect student outcomes, especially in light of student-directed styles versus teacher-directed styles. However, the field of research based on GummÂ’s model is relatively new and therefore limited in breadth. This study may connect and expand these three fields, fill in some of these gaps in knowledge, and provide information wh ich may not only be beneficial to band
46 directors, but may also hold implications fo r personality types and teaching styles which are predictors for success for all music educators.
47 Chapter 3: Methodology This study was a descriptiv e correlational study, examining the strength of the relationship between aspects of high school band directorsÂ’ personality, teaching style, and festival scores. This st udy also examined the strength of relationships between balance and festival scores. Survey respons es were gathered and correlations were calculated among the variables. Population and Sample The target population of in terest in this study was all high school band directors in the state of Florida who directed both con cert and marching band programs. I distributed the link to the online survey instrument to the entire population of 384 high school band directors in Florida. The re turn rate was 45.9%; sufficient to produce valid and reliable statistical analysis for the thirty-eight predictor va riables included in this study. The Variables The primary categories of variables in this research were band director personality type, teaching style, festival ratings, festival attendance, and balance. There were seven criterion variables which incl uded marching and concert festiv al ratings at the district level and the competitive or state level, as well as frequency of attendance at those events and the balance between marching and concert band. There were thirty-eight predictor variables. Eight of these va riables were teaching styles, and the other thirty were personality facets. Four additional demographi c variables were included for preliminary
48 analysis and to help describe the sample: gender, experience, level of education, and primary instrument of the subject. Detail ed descriptions and working names for the variables divided by variable type are liste d below: criterion va riables, predictor variables, and demographic variables. Criterion Variables A quantifiable assessment of the bandÂ’s pe rformance (festival and contest ratings) was used to determine a bandÂ’s performance success in this research. In Florida, the majority of bands participate in district le vel Music Performance Assessments, or MPAs (often referred to by the more familiar name Â“festivalsÂ” which is used throughout this study for consistency) for both marching and concert band performances. These festivals are organized through the Florida Bandmast ers Association (FBA). Judges who are experienced professional music educators (a nd often are certified adjudicators by the FBA) give ratings of superior, excellent, good, fair, or poor. Some bands also choose to perform in competitive marching band events such as those sponsored by the Florida Marching Band Coalition (FMBC) or Bands of America (BoA). Scores from the FMBC and BoA are numerical, on a scale from 40100 (100 being the highest), and bands are ranked in order from highest to lowest at each event. This is in contrast to FBA sponsored events where bands earn a rating which may be shared by many other bands which results in a non-competitive atmosphere where the goal is to reach a high standard of performance rather than to score higher than other bands. In this study, ratings from FBA festival and FMBC competitions were included for the purpose of consistency. The most recently published ratings were used, although to improve reliability I used a mean of the
49 bandÂ’s ratings for up to three years if the dir ector was at that school for more than one year. The FBA categorical ratings of Superior Excellent, Good, Fair, and Poor from each judge were converted to a numerical eq uivalent, and the final score was calculated based on these numbers. Since the sight-read ing judge in concert MPAs was weighted slightly less than the stage judges, this aff ected the final ratings for bands earning what otherwise seemed to be the same ratings. Fo r example, two bands could earn two ratings of Superiors and two ratings of Excellent, ye t one might earn a final rating of Superior, and one might earn a final rating of Excellent. If there were two ratings of Excellent from the stage judges then the fina l ratings would be Excellent. Ho wever, if the two ratings of Excellent came from one stage judge and th e sight-reading judge, the score remained a Superior. To reflect this in my numerical system, the former example would have a final rating of 1.51, while the latter example would be given a final rating of 1.49. Similarly, a band might earn an overall Excellent rating if they earned two ratings of Superior and two ratings of Excellent if one of the Superior ratings was from the sight-reading judge, but the same rating would be awarded to a band earning two ratings of Good and two ratings of Excellent if one of the Good rati ngs was from the sight-reading judge. In this research, the numerical ratings drew a sharp distinction between these two ratings as the former would earn a 1.49 and the latter would earn a 2.49. On a five-poi nt scale, this was significant. Figure 3 summarizes the transfor mation of the categorical FBA ratings to numerical ratings.
50 Concert Band Ratings Judge 1 Judge 2 Judge 3 Sight Reading Final Rating School A FBA ratings Superior Superior Superior Superior Superior numerical ratings 1 1 1 1 1 School B FBA ratings Superior Superior Excellent Excellent Superior numerical ratings 1 1 2 2 1.49 School C FBA ratings Superior Excellent Excellent Superior Excellent numerical ratings 1 2 2 1 1.51 School D FBA ratings Good Excellent Excellent Good Excellent numerical ratings 3 2 2 3 2.49 Figure 3: FBA Concert Rating Conversion Example Similarly, music judges in marching ba nd MPAs are weighted higher than the marching judge and general effect judge. Numeri cal scores were adjusted to reflect this weighting. Figure 4 demonstrates the transf ormation of the FBA marching MPA ratings to numerical ratings. Marching Band Ratings Music 1 Music 2 Marching General Effect Final Rating School A FBA ratings Superior Superior Superior Superior Superior numerical ratings 1 1 1 1 1 School B FBA ratings Superior Superior Excellent Excellent Superior numerical ratings 1 1 2 2 1.49 School C FBA ratings Excellent Excellent Superior Superior Excellent numerical ratings 2 2 1 1 1.51 School D FBA ratings Excellent Excellent Excellent Superior Excellent numerical ratings 2 2 2 1 1.75 School E FBA ratings Good Excellent Excellent Good Excellent numerical ratings 3 2 2 3 2.5 Figure 4: FBA Marching Ratings Conversion Example Marching Ratings This variable is a rating category refe rring to Florida Bandmasters Association (FBA) district-level marching music perfor mance assessment. This reflects only the ratings of the two music j udges, the marching and maneuve ring judge, and the general
51 effect judge, which the FBA has ruled as the only four captions wh ich count toward the final rating. Many bands are also given ratings exclusively for the percussion section and auxiliary units such as the colo r guard, but those are not factor ed into the final rating with FBA. Concert Ratings This variable is a rating category referri ng to FBA district-level concert music performance assessment. This is composed of the three stage judges as well as the sightreading judge. Final ratings were calculat ed according to FBA rules. For bands with multiple concert bands, the given yearÂ’s mean rating was a mean of all of the bandsÂ’ ratings which participated that year. Competitive Marching Ratings This variable is a rating category refe rring to non-FBA sponsored marching band competitions which result in continuous num erical ratings of 40-100 rather than the FBAÂ’s categorical ratings. These were even ts sponsored by the Florida Marching Band Coalition (FMBC). State Concert Band Ratings This variable is a rating category refe rring to FBA state-level concert music performance assessment. In order to qualify to participate in this event, a band must receive a final rating of supe rior at the district level concert band music performance assessment. This rating was composed of thr ee stage judgesÂ’ ratings. Final ratings were a mean of the numerical equiva lent of the judgesÂ’ ratings.
52 Marching Competition Attendance Frequency This is the mean number of annual co mpetitive (non-FBA) marching events. This was a number between 0 and 10 (maximum number of weeks of FMBC competitions). Mean High Score in Marching Competitions This is a mean of the highest scores a band earns each year in which it participated in competitive marching band events. This number was between 40 and 100. State Concert Festival Attendance Frequency This variable is the percentage of time s the subject participated in the state concert band festival during the three years sa mpled. A percentage was used in place of a number since not all subjects were at the same school for the past three years. Balance This categorical variable is an explor atory construct which indicates which of three categories a subject fits based on marching and concert band ratings and participation. This represents how the subj ectÂ’s band ratings are ba lanced: earning higher ratings in concert band, higher ratings in marching band, or balanced between the two. The categories are marching-oriented, concer t-oriented, and balanced. Subjects were assigned a category of balance according to th e following guidelines: if a subjectÂ’s mean marching band rating was equal to or more th an 0.5 points higher than subjectÂ’s mean concert band rating, and the subjectÂ’s band participates in a mean of one or more competitive marching band events per year, and the subject has not participated in state concert band festival in the past three years, then the subject was classified as Â“marching oriented.Â” If the subjectÂ’s mean concert ba nd rating was equal to or more than 0.5 points higher than subjectÂ’s mean marching band rati ng, and the subject participated in state
53 concert band festival at least once in th e past three years, and the subjectÂ’s band participates in a mean of less than one competitive marching band event per year, then the subject was classified as Â“concert orient ed.Â” All subjects who were not classified Â“marching orientedÂ” or Â“concert oriented Â” were classified as Â“balanced.Â” Predictor Variables There were thirty-eight predictor vari ables which fall into two categories. Personality factors make up the first category of predictor variables. This is the FiveFactor Model of personality derived from the International Personality Item Pool Representation of Costa & McCraeÂ’s NE O-PI-R, or IPIP-NEO, by John A. Johnson (2005). The five factors consiste d of 30 facets. Personalities of individuals were reported as a number between 1 and 5 on each of the thir ty facets. These thirty facets are Anxiety, Anger, Depression, Self Consciousness, Im moderation, Vulnerability, Friendliness, Gregariousness, Assertiveness, Activity, Exci tement Seeking, Cheerfulness, Imagination, Artistic Interest, Emotion, Adventurousness, Intellect, Liberalism, Trust, Morality, Altruism, Cooperation, Modesty, Sympathy, Self Efficacy, Orderliness, Dutifulness, Achievement Striving, Self Discipline, and Cautiousness. Higher numbers indicate a greater degree of the personality facet present in the subject. The second category of pred ictor variables is teachi ng style. These variables indicate the subjectÂ’s strengt h on eight teaching styles as determined by GummÂ’s (2003) Music Teaching Style Inventory (MTSI). Each of the eight styles was represented by a numerical score between 1 and 5. These teaching styles are Assertive Teaching, Nonverbal Motivation, Time Efficiency, Positive Learning Environment, Group Dynamics, Music Concept Learning, Artis tic Music Performance, and Student
54 Independence. Higher numbers for each teachi ng style indicated that the subject claimed to more frequently exhibit behaviors or attitudes relevant to that teaching style. Demographic Variables Demographic information were collec ted from subjects and used in the preliminary analysis to help describe the group of subjects who participated in the research. The demographic variables included gender, years of teaching experience, level of education, and what instrument (including voice) the subject considered as his or her primary performance medium. The f our demographic variables were: Gender Subjects choose male or female for this categorical variable. Experience This was the number of years the subject has taught, rounded to the nearest whole number, and including the curren t school year as a full year. Education The ordinal variable Educati on represented the highest le vel of education attained by the subject. Subjects chose from a list including high school diploma, associateÂ’s degree, bachelorÂ’s degree, masterÂ’s degr ee, specialist degree or doctoral candidate (ABD), or doctoral degree. Instrument This categorical variable represented the primary performance medium of the subject. Subjects chose from a list of flut e, oboe, bassoon, clarinet, saxophone, trumpet, horn, trombone, euphonium, tuba, percussion, pi ano/organ/harpsichor d, voice, stringed instrument, or other instrument.
55 The Survey Instrument The survey instrument for this study wa s an internet-based researcher-created survey. The instrument consisted of thr ee major parts: the Music Teaching Style Inventory, the IPIP-NEO, and school information. The Music Teaching Style Inventory (M TSI) was created by Alan Gumm and published in his book Music Teaching Style in 2003. The MTSI has been reproduced in the survey instrument by permission from th e copyright holder. The MTSI was meant to help music teachers determine to what de gree they employ the eight teaching styles. There were a total of 57 items on the MTSI. Th ere were seven questions for each of eight dimensions, along with the first question whic h was designed to prime the subject for the remaining questions. These eight dimensions were Assertive Teaching (represented by test items 2, 10, 18, 26, 34, 42, 50), Nonverbal Motivation (items 3, 11, 19, 27, 35, 43, 51), Time Efficiency (items 4, 12, 20, 28, 36, 44, 52), Positive L earning Environment (items 5, 13, 21, 29, 37, 45, 53), Group Dynami cs (items 6, 14, 22, 30, 38, 46, 54), Music Concept Learning (items 7, 15, 23, 31, 39, 47, 55), Artistic Music Performance (items 8, 16, 24, 32, 40, 48, 56), and Student Independence (items 9, 17, 25, 33, 41, 49, 57). The items were statements about teaching behavi ors such as Â“Communicate an awareness of student behavior.Â” Subjects took the MTSI at their own p aces; all 57 questions were available simultaneously and answers can be changed. There was no time limit. Subjects were asked to select a response from a five point Likert-type scale which represented how often they engaged in this behavior. The fi ve choices were Never, Rarely, Sometimes, Often, and Always, and each corresponded with a numerical value (one through five, respectively). Scores were calculated by tota ling the numerical values for each of the
56 eight dimensions and then dividing the total by seven. The result was a mean value between 1 and 5 which indicated how ofte n the subject employed the given teaching dimension in the classroom. The MTSI has been validated in a number of ways since its conception. A pilot study established face validity for the list of teaching behaviors, and a national sample established construct validity for the current eight dimensions (Gumm, 1993). Predictive validity was established in a correlation betw een music teaching styles and music festival ratings (Gumm, 2003b). Shared variance and lo gical relationships between the MTSI and a college teacher evaluation support this pr edictive validity (Gum m, 2004a). The MTSI was compared to AsmusÂ’ measures of motiv ation for music and KolbÂ’s Learning Style Inventory, indicating the MTSI measured mu sic teaching style and not motivation for music or learning styles (Gumm & Essmann-Paulson, 2001; Gumm, 2004b). Concurrent validity existed between the MTSI dimensions and student opinion survey ratings of teacher effectiveness (Gumm, 2007). The alpha reliabilities reported for each of the teaching styles in the 2007 study were .751 for Assertive Teaching, .819 for Nonverbal Motivation, .792 for Time Efficiency, .787 for Positive Learning Environment, .725 for Group Dynamics, .828 for Music Concept Learning, .769 for Artistic Music Performance, and .864 for Student Independence. The International Personalit y Item Pool representation of the NEO, or IPIP-NEO, is a public domain representation of the NEO-PI-R designed by Co sta & McCrae (1992). The short version (120 items) in this st udy was designed by John A. Johnson (2003), and was included in the survey instrument. The IPIP-NEO used here was developed in 2003 and was derived from the IPIP which was developed in 1999 by Lewis R. Goldberg.
57 The IPIP-NEO was designed to give an indication of a subjectÂ’s personality based on the Five-Factor Model of personality with its thirty facets. The short version employed in this study contains 120 items. This repres ented four questions per facet. Each item was a short sentence fragment such as Â“Like bei ng in large groups of pe opleÂ” and subjects had five response choices from which to selec t: Â“very inaccurate,Â” Â“inaccurate,Â” Â“neither accurate nor inaccurate,Â” Â“accurate,Â” and Â“ver y accurate.Â” Items represented the various dimensions and were shuffled so that item s representing the same dimension are rarely adjacent in the survey. Surveys were admi nistered electronically at the subjectÂ’s convenience. There was no time limit to complete the 120 items. Many items were presented both positively and negatively (e .g. Â“I find it difficult to start conversationsÂ” and Â“I find it easy to start conversations Â”). Responses had a co rresponding numerical score (1 for Â“very inaccurateÂ” and 5 for Â“v ery accurateÂ”). The mean score for all responses for a given dimension indicated the strength of that dimension or facet in the subject. Those that were presented negativel y must have the numeri cal representation of the response reversed when scoring. The IPIP-NEO indicat ed a subjectÂ’s personality dimension along a continuum represented numer ically between 1 and 5. This was much more useful in determining correlations th an the polarized categories of the MBTI. Scores closer to Â“5Â” indicate a subject tende d to show more charac teristics of a given dimension, while scores closer to Â“1Â” indica ted a tendency towards th e opposite trait. If a subject scored a Â“5Â” on Extraversion, then he or she selected answers which indicated an extremely high level of Extraver sion. If a subject scored Â“1 Â” on Extraversion, then he or she selected answers which would indicate an extremely low level of Extraversion and a correspondingly high leve l of Introversion.
58 The IPIP-NEO short version has slightly lower levels of reliability compared to the long (300-item) version, but still retain s satisfactory levels of reliability. Alpha reliabilities were determined from a nationa l sample of 20,993 subjects and are: Anxiety (.71), Anger (.77), Depression (.80), Self Consciousness ( .63), Immoderation (.69), Vulnerability (.70) Friendliness (.77), Gregariousness (.60), Assertiveness (.75), Activity (.68), Excitement Seeking (.67), Cheerfulness (.71), Imagination (.70), Artistic Interest (.72), Emotion (.67), Adventurous ness (.66), Intellect ( .78), Liberalism (.76), Trust (.70), Morality (.62), Altruism ( .65), Cooperation (.56), Modesty (.63), Sympathy (.68), Self Efficacy (.57), Orderliness (.76) Dutifulness (.47), Achievement Striving (.68), Self Discipline (.66), and Cautiousness (.70). Protocol validity for the IPIP-NEO wa s determined by comparing results with results of other psychological measures whic h had been done by the subjects previously, as well as by correlating the items of th e NEO-PI-R and the IPIP-NEO. The NEO PI-R on which the IPIP-NEO is based is one of the most widely used and well-validated personality inventories (Johnson, 2005), a nd the average correlation between corresponding scales of the extensively vali dated NEO PI-R and the IPIP-NEO is .73 (.94 when corrected for attenuation due to unreliabi lity). This high corre lation indicates a high degree of validity for the IP IP-NEO (Goldberg, 1999). The remaining items on the survey instrument were intended to gather information about the subjectÂ’s schools as well as demographic information regarding gender, experience, education, and instrument Subjects were asked to indicate at which Florida high school they taught for each school year since 2000-2001. Based on this information, band rating and participation da ta were entered into SPSS from publicly
59 available FBA and FMBC score archives, consis ting of the most rece nt three-year period at the same school. If three years of data were not available, then the most recent year or two years were used. The final section aske d the subject to sel ect responses to the demographic variables gender, years of expe rience, highest degree earned, and primary instrument. Additionally, the subj ect was asked if he or she w ould like to be informed of their personality and music teaching style prof ile results. The subject had the option to type in an email or postal address where the information could have been sent, or leave the space blank if they were not interested. There was a spa ce at the end for Â“other inputÂ” where the subject had the opport unity to leave comments. Data Collection Data were collected electronically thr ough a researcher-designed survey created through SurveyMonkey. This web service provide d a link to the survey instrument which was inserted into an email inviting band director s to participate. In order to proceed with the survey, potential subjects were require d to acknowledge that participation was voluntary and that they gave their consent. Sp ecific instructions fo r items and sections were included in the online survey. The surv ey was distributed via email to all currently active and recently retired (less than five years) high school ba nd directors in the state of Florida whose email addresses are listed in the Florida BandmasterÂ’s Association Member Directory. The link to the survey remained open for a period of seven weeks following the date the last email was sent. Th ree weeks into the data collection period, a second email was sent out by Survey Monke y to those who had not yet responded to please complete the survey. During the fifth w eek of the data collection process, a third and final request was sent out by Surv ey Monkey to non-responders to request
60 participation. At the end of seven week s the survey was closed and data were downloaded. No personally identif iable information was gathered in the survey, so all data collected were fully anonymous. Furthe rmore, none of the information gathered through the survey was of a se nsitive nature. Subjects were expected to have spent approximately twenty minutes completing the survey. Data Analysis Once the raw data from the survey we re downloaded, they were entered into SPSS. CronbachÂ’s alpha was calculated to determ ine the reliability of each of the five personality domains, eight teaching styles, and four types of band ratings. The following sections included the ways in which the raw data were transformed to create the criterion and predictor variables. IPIP-NEO The 120 test items were scored to determine final scores for each of the thirty personality facets. Each subjec t had a score between 1 and 5 for each of the thirty facets of personality. MTSI The 57 test items were scored to determ ine final scores for each of the eight teaching styles. Each subject had a score be tween 1 and 5 for each teaching style. District FBA Concert and Marching Band Ratings To compute the final rating for a given band in a given year, the four judgesÂ’ ratings (not including final rating as stated by the subject) for each of the subjectÂ’s bands was averaged. Each subject had a mean of these band ratings, between 1 and 5 (1 being Â“highÂ”).
61 Competitive Marching Band Events A mean of the number of competitive marching band events a band has participated in over the past three years wa s calculated. The mean of the highest rating from each year was also reported. State FBA Concert Band Events This is the total number of times the subj ect reported attendin g state concert band festival during the last period of up to thr ee years he or she was at the same school, divided by the number of years (up to three) the subject was at the school. A band can only attend this event once pe r year. The mean rating fo r all the subjectsÂ’ bands participating during the same ti me frame was also reported. State Concert Band Ratings These data did not address the research questions and were not used beyond the preliminary analysis. Mean High Score in Marching Competitions These data also did not a ddress the research questions and were not used beyond the preliminary analysis. Analysis of the Variables The variables included the thirty facet s of personality, eight teaching styles, a mean concert band rating, a mean marching band rating, a mean frequency of participation in competitive marching band events, a mean competitive marching band rating, a total number of state FBA concert band events, and a mean state concert band rating for each subject. There were also de mographic variables of gender, experience, education, and instrument for each subject. The balance variable was determined from the
62 marching and concert band data for each subj ect, and was the final category of data included for each subject for a total of fo rty-nine data points for each subject. Before examining the data to answer the research questions, I presented a preliminary analysis of the data which incl uded such descriptive statistics as means, standard deviations, skewness, a nd kurtosis for all 49 variables. In addition to descriptive statistics, the preliminary analyses included reliability data for personality dimensions, teaching styl es, and band scores. To present appropriate context prior to answering the research questi ons, a correlation table included correlations among personality facets, teaching styles, marching ratings, concert ratings, mean number of competitive marching events, number of state concert events, mean competitive marching rating, and mean state concert festival scores. The research questions were addressed following the preliminary analysis of the data. To answer the first four questions, Â“What kinds of re lationships exist between band directorsÂ’ personality types or teaching styles and their concert band ratings?,Â” Â“What kinds of relationships exist between band dire ctorsÂ’ personality type s or teaching styles and their marching band ratings?,Â” Â“In what wa ys do band directorsÂ’ personality types or teaching styles contribute to the number of stat e concert band events in which their bands participated?,Â” and Â“In what ways do band dir ectorsÂ’ personality type s or teaching styles contribute to the number of competitive marching band events in which their bands participated?,Â” the data were analyzed using multiple regression for the predictor variables of personality (anxiety, anger, de pression, self consciousness, immoderation, vulnerability, friendliness, gr egariousness, assertiveness, activity, excitement seeking, cheerfulness, imagination, artistic inte rest, emotion, adventurousness, intellect,
63 liberalism, trust, morality, altruism, c ooperation, modesty, sympathy, self efficacy, orderliness, dutifulness, achievement stri ving, self discipline, and cautiousness) and teaching styles (assertive teaching, nonverbal motivation, time efficiency, positive learning environment, group dynamics, mu sic concept learning, artistic music performance, and student independence), on th e criterion variables of marching ratings, concert ratings, state FBA concert festival particip ation, and FMBC competitive marching event particip ation, respectively. The fifth research question, Â“In what ways do band directorsÂ’ personality types or teaching styles contribute to the bala nce between marching and concert band participation and scores?Â” compared the pred ictor variables of pe rsonality facets and teaching styles, on the criterion variable of ba lance. Since the three categories of balance are categorical instead of c ontinuous, this question was addressed using discriminant analysis.
64 Chapter 4: Results of the Data Analysis The data analysis and results in this chapter begin with a preliminary analysis, which displays demographic information as well as descriptive statistics for the variables, and concludes with the results pertaining to the research problems. Narrative description followed by tables and graphs present the data for each section. A link to the Survey Monkey-based survey instrument was sent to the entire population of 384 high school band di rectors in Florida. The fi rst request resulted in 114 responses. Four weeks later, a second em ail was sent through Survey Monkey, which resulted in 40 additional responses. Three w eeks after the second ema il, a third and final email request was sent from Survey Monkey, wh ich resulted in 34 a dditional responses. Of the 188 total responses, 10 responses did not contain enough information to be of any use, and two subjects submitted two surveys. There were a total of 176 usable surveys, which represented approximately 45.8% of the population. Florida BandmasterÂ’s Association (FBA) district numbers were iden tified for the subjectsÂ’ schools and each of the 21 FBA districts were represented, reflecting the wide variety of communities from urban centers such as Miami, Tampa, Orlando, and Jacksonville to ru ral central and north Florida. Table 1 indicates response rates by dist rict (note that Distri ct 20 is not included; District 20 is primarily made up of the Da de County private school s and schools in the Florida Keys, few of which participate regularly in FBA activities).
65 Demographic information submitted by participants included gender, academic degree, years of teaching experience, and what instrument the teacher primarily plays. Out of the 176 valid responses, 148 were male representing 84.1% of the sample, and 28 were female, approximately 15.9% of the sample. This is a very accurate representation of the population where females constitute approximately 15.9%. Table 1 Responses Frequency and Percentage by Fl orida Bandmasters Association Districts ________________________________________________________________________ Dist. Counties in district n response ______________________________________________________________________________________ 1 Escambia, Santa Rosa, Okaloosa 8 44.4% 2 Walton, Holmes, Jackson, Bay, Washington, Gulf, Liberty, Calhoun, Franklin 11 64.7% 3 Leon, Gadsden, Hamilton, Jefferson, Wakulla, Lafayette, Taylor, Madison, Hamilton, Suwannee 6 50.0% 4 Alachua, Dixie, Levy, Gilchrist, Columbia Union, Baker, Bradford 9 64.3% 5 Pasco, Hernando, Citrus 8 47.1% 6 Seminole, Volusia 8 50.0% 7 Hillsborough 19 59.4% 8 Orange 10 47.6% 9 Pinellas 5 25.0% 10 Brevard, Osceola 9 40.9% 11 Manatee, Sarasota, Charlotte, DeSoto, Hardee 8 44.4% 12 Polk 8 53.3% 13 Indian River, Martin, St. Lucie, Highlands, Glades, Okeechobee 5 38.5% 14 Palm Beach 8 40.0% 15 Broward 12 36.4% 16 Dade 9 33.3% 17 Duval, Nassau 9 60.0% 18 Lee, Collier 7 35.0% 19 Marion, Sumter, Lake 9 45.0% 21 St. Johns, Flagler, Clay, Putnam 8 53.3% Total 176 ______________________________________________________________________________________ Subjects were asked to indicate their highe st level of academic degree, from the choices high school diploma, Associates De gree, BachelorÂ’s Degr ee, MasterÂ’s Degree, Specialist or incomplete Doctoral Degree, a nd Doctoral Degree. None of the respondents chose high school diploma, Asso ciates Degree, or Doctoral Degree, and those choices are
66 no longer included in the data analysis. There were 96 subjects who indicated BachelorÂ’s, representing 55.5% of the sample, 73 subjects who indicated MasterÂ’s, which represents 42.2% of the sample, and 4 subjects indicated Specialist or incomple te Doctoral degree, (hereafter abbreviated as Â“S pecialistÂ”) representing 2.3% of the sample. Three subjects did not report their high est academic degree. Subjects were asked to indicat e the instrument he or she considered to be his or her primary instrument from a list incl uding flute, oboe, bassoon, clarinet, saxophone, trumpet, horn, trombone, euphonium, tuba, perc ussion, piano/organ/ha rpsichord, stringed instrument, voice, and other. The final two c hoices, voice and other were not selected by any subjects and will not be included in further discussion. Instrument information is displayed in Table 2 in the order of most frequently selected choices. Table 2 InstrumentsFrequencies and Percentage ____________________________________ Instrument n percent ____________________________________ Trumpet 51 29.5 Saxophone 23 13.3 Trombone 20 11.6 Percussion 18 10.4 Clarinet 16 9.2 Horn 11 6.4 Euphonium 11 6.4 Tuba 9 5.2 Bassoon 5 2.9 Flute 4 2.3 Piano/Keyboard 3 1.7 Oboe 1 0.6 Stringed Instrument 1 0.6 Total 173 100.0 ___________________________________ Note: 3 subjects did not report instrument
67 The only demographic variable where responses were on a scalar continuum rather than in discrete categories was teachi ng experience. The mean number of years of teaching experience reported by the 173 subjec ts who completed this item on the survey was 12.77 years ( SD was 9.94 years). The skewness was .93, and kurtosis was -.09. Teaching experience ranged from 1 year to 40 years. Descriptive statistics fo r the criterion variables FB A marching band festival, (Â“MarchingÂ”), FBA concert band festival, (Â“ConcertÂ”), FMBC competitive marching band attendance (Â“FMBC attendÂ”), FMBC ma rching band mean score (Â“FMBC scoreÂ”), state FBA concert band attendance (Â“State c oncert attendÂ”), and st ate FBA concert band mean ratings (Â“State concert scoreÂ”) are pr esented in Table 3. Number of responses, mean, standard deviation, skewne ss, and kurtosis, are included. Table 3 Descriptive Statistics fo r Criterion Variables ________________________________________________ variable n M SD Skew. Kurt. ________________________________________________ Marching 163 1.45 .51 1.29 1.28 Concert 167 1.78 .61 1.16 1.74 FMBC attend. 175 1.34 1.31 .71 -.67 FMBC score 124 72.10 9.48 -.09 -.98 State concert attend. 175 .33 .40 .75 -1.10 State concert score 81 1.76 .57 1.07 2.01 ________________________________________________ It is noteworthy that while the same rating system is used by the FBA for both Marching and Concert festivals, the sample of directors overall scored higher for Marching (1.45, or a low Superi or) than for Concert (1.78, a high Excellent). Subjects reported a mean FMBC frequency of 1.34 competitive marching band events per year,
68 although the standard deviation is nearly the same as the mean (1.31). The mean yearly score at FMBC is 72.10, which is just a bove the Â“SuperiorÂ” classification (FMBC Superior is between 70.00 and 84.99). Unlike FBA, this is not the hi ghest classification though, which is Â“DistinctionÂ” (scores of 85.00-100.00). The sample reported a mean FBA state concert festival at tendance rate of .33, which was the equivalent of going to state concert festival once every three year s. The mean rating for those who did attend state concert festival (81 subjects) was 1.76, which was a high Excellent. Descriptive statistics of the predictor va riables of teaching styles and personality are included in Table 4. The first eight variables, Assertive Teaching, Nonverbal Motivation, Time Efficiency, Positive Learning Environm ent, Group Dynamics, Music Concept Learning, Artistic Music Performance, and Student Independence are the eight teaching styles. The next 30 predictor variable s are the sets of six facets for each of the five personality dimensions: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Th ese thirty facets are Anxiety, Anger, Depression, Self-Consciousness, Immode ration, Vulnerability, Friendliness, Gregariousness, Assertiveness, Activity, Exci tement Seeking, Cheerfulness, Imagination, Artistic Interest, Emotion, Adventurousness, Intellect, Liberalism, Trust, Morality, Altruism, Cooperation, Modesty, Sympathy, Se lf-Efficacy, Orderliness, Dutifulness, Achievement Striving, Self-Disci pline, and Cautiousness. Nineteen subjects completed the first por tion of the survey instrument, which contained the MTSI, but quit before comp leting the personality inventory, which accounts for the disparity in numbers between the teaching styles and the personality dimensions. All items are Likert-type scale items with possible values from 1 to 5.
69 Table 4 Descriptive Statistics for Predictor Variables _______________________________________________________________________ Predictor variable n M SD Skew. Kurt. _______________________________________________________________________ Teaching Styles Assertive Teaching 176 4.00 .52 -.11 -.47 Nonverbal Motivation 176 3.89 .47 -.01 -.01 Time Efficiency 176 4.22 .46 -.32 -.61 Positive Learning Environment 176 4.22 .48 -.41 -.21 Group Dynamics 176 3.27 .55 .07 .19 Music Concept Learning 176 3.75 .51 -.46 1.02 Artistic Music Performance 176 3.53 .56 -.16 .32 Student Independence 176 3.43 .62 .12 .00 Personality DimensionNeuroticism Anxiety 157 2.81 .85 .18 -.64 Anger 156 2.97 .95 -.13 -.69 Depression 156 2.04 .80 .66 .17 Self Consciousness 156 2.92 1.04 -.05 -.87 Immoderation 155 2.73 .77 .08 -.03 Vulnerability 155 2.25 .81 .37 -.44 Personality DimensionExtraversion Friendliness 157 3.82 .78 -.48 -.53 Gregariousness 156 3.02 1.01 -.03 -.94 Assertiveness 155 4.19 .61 -1.19 2.59 Activity 155 3.64 .65 -.16 -.44 Excitement Seeking 155 2.95 .70 .14 -.13 Cheerfulness 155 3.95 .62 -.28 -.52 Personality DimensionOpenness to Experience Imagination 157 3.48 .84 -.12 -.55 Artistic Interest 156 4.05 .64 -.88 1.28 Emotion 155 3.78 .61 -.27 -.29 Adventurousness 155 2.98 .82 .13 -.28 Intellect 155 4.05 .83 -.69 -.12 Liberalism 155 2.48 .98 .09 -.99 Personality DimensionAgreeableness Trust 157 3.66 .80 -.66 .14 Morality 156 4.36 .61 -.96 .70 Altruism 155 4.26 .55 -.74 .66 Cooperation 155 3.85 .83 -.59 -.04 Modesty 155 3.13 .84 .19 -.84 Sympathy 155 3.73 .69 -.70 .96 Personality DimensionConscientiousness Self Efficacy 157 4.30 .47 -.49 -.21 Orderliness 156 3.46 1.03 -.29 -.86 Dutifulness 155 4.52 .49 -.69 -.39 Achievement Striving 155 4.61 .44 -1.01 .19 Self Discipline 155 3.88 .65 -.34 -.79 Cautiousness 155 3.82 .91 -.65 -.19 _______________________________________________________________________
70 The first four teaching styles are classifi ed by Gumm as teacher-oriented, and the second four are classified as student-oriented. Subjects reported higher mean ratings on the teacher-oriented styles than on the student-ori ented styles. Eight personality facets were higher than 4.00 and are listed from highe st to lowest: achievement striving ( M =4.61), dutifulness ( M =4.52), morality ( M =4.36), self-efficacy ( M =4.30), altruism ( M =4.26), assertiveness ( M =4.19), intellect ( M =4.05), and artistic interest ( M =4.05). The three lowest facets were depression ( M =2.04), vulnerability ( M =2.25), and liberalism ( M =2.48). Descriptive statistics for the criterion and predictor va riables are also broken down by the representative demographic groups and are located in Appendices A through I. These appendices present criterion scor es by gender, by academic degree, and by instrument. Following those are appendices wh ich present predictor variables by gender, academic degree, and instrument. Reliability coefficients were calcula ted from the items on the Music Teaching Style Inventory and compared with existi ng reliability inform ation. Teaching style reliabilities were published by the author of the MTSI (Gumm, 2003b) and are presented alongside reliabiliti es from this study in Table 5. Similar reliabilities emerged for most of the teaching styles except for Nonverbal Motivation (.66), which was lo wer than GummÂ’s findings ( .82). No individual itemÂ’s removal from the Nonverbal Mo tivation items would have impr oved the reliability of that teaching style. The reliability for Music Con cept Learning (.74) was also lower than the reliability reported by Gumm (.83), although being above .70 the re liability is still satisfactory. The results of the reliability pr ocedure indicated the removal of some test
71 items would have improved reliability slightly on two dimensions. Since these teaching styles already had satisfactor y reliability, the items were not removed. In the Artistic Musical Performance teaching style, deleti on of question 5, Â“Develop musical skills through physical manipulationÂ” w ould have raised the reliabil ity slightly, from .74 to .76. For Student Independence, deletion of th e question 5, Â“Use discussion and dialogue instead of one-way lectureÂ” would have cha nged the reliability sl ightly, from .85 to .86. Reliability for Assertive Teaching, Nonverbal Motivation, Time Efficiency, Positive Learning Environment, Group Dynamics, and Music Concept Learning would have only decreased with removal of any survey items. Item to teaching style correlations were calculated for the MTSI and are displayed in Table 6. Inter-item correlation matrices for teaching style can be found in Appendix J. Table 5 Reliability Data (CronbachÂ’s ) for the Music Teaching Style Inventory ________________________________________________________________________ MTSI dimension this study Gumm (2003b) ________________________________________________________________________ Assertive Teaching .75 .75 Nonverbal Motivation .66 .82 Time Efficiency .75 .79 Positive Learning Environment .79 .79 Group Dynamics .78 .73 Music Concept Learning .74 .83 Artistic Music Performance .74 .77 Student Independence .85 .86 ________________________________________________________________________
72 Table 6 Item-Total Correlations with Teaching Styles for the Music Teaching Style Inventory ________________________________________________________________________ Item Number MTSI dimension 1 2 3 4 5 6 7 Assertive Teaching .66 .63 .68 .72 .57 .66 .54 Nonverbal Motivation .60 .63 .47 .66 .58 .58 .53 Time Efficiency .57 .64 .59 .72 .61 .60 .70 Positive Learning Environ. .59 .64 .65 .67 .70 .72 .72 Group Dynamics .60 .65 .56 .72 .72 .58 .75 Music Concept Learning .57 .64 .57 .66 .67 .60 .69 Artistic Music Performance .65 .68 .73 .64 .47 .60 .64 Student Independence .75 .79 .74 .73 .55 .73 .79 ________________________________________________________________________ These item-total reliabilities are gene rally moderately strong, ranging from .60 to .79 for the majority of the teaching styles. It ems are particularly strongly correlated for Student Independence, with most items (ex cept item 5) being higher than .70. The only two items on the MTSI with lower correlati ons with their teaching style than .50 are Nonverbal Motivation item 3, and Artistic Music Performance question 5 (both with r = .47). Reliability coefficients were also calc ulated from the items on the IPIP-NEO and compared with existing reliability information. Reliability for the personality facets were published by Johnson (2005) and are presented al ongside reliabilities fr om this study in Table 7. Reliabilities for personality were suffi ciently high for many facets, and were higher than in JohnsonÂ’s study (which incl uded approximately 21,000 subjects) on 24 of the 30 facets. Only seven facets had reliability coefficients lower than .70, and morality
73 Table 7 Reliability Data (CronbachÂ’s ) for the IPIP-NEO Personality Facets _____________________________________________________________ IPIP-NEO dimension this study Johnson (2005) _____________________________________________________________ Neuroticism Anxiety .72 .71 Anger .85 .77 Depression .83 .80 Self Consciousness .72 (.69)* .63 Immoderation .61 .69 Vulnerability .73 .70 Extraversion Friendliness .80 .77 Gregariousness .83 .60 Assertiveness .80 .75 Activity .53 .68 Excitement Seeking .64 .67 Cheerfulness .74 .71 Openness to Experience Imagination .76 .70 Artistic Interest .57 .72 Emotion .43 .67 Adventurousness .75 .66 Intellect .74 (.66)* .78 Liberalism .76 .76 Agreeableness Trust .87 .70 Morality .67 .62 Altruism .70 .65 Cooperation .69 .56 Modesty .75 .63 Sympathy .70 .68 Conscientiousness Self Efficacy .72 .57 Orderliness .85 .76 Dutifulness .72 (.58)* .47 Achievement Striving .71 .68 Self Discipline .70 .66 Cautiousness .89 .70 _____________________________________________________________ *indicates reliability prior to removal of items
74 (.67) and cooperation (.69) were quite clos e. The lowest five reliabilities were on excitement seeking (.64), immoderation (.61), artistic interest ( .57), activity (.53), and emotion (.43). The reliability for three facet s increased substantially by eliminating one survey item from each facet. These facets we re dutifulness (increased from .58 to .72), self consciousness (increased from .69 to .72), and intellect (increased from .66 to .74). Pearson product-moment correlations between survey items and facets are indicated in Table 8. Inter-item correlations for personal ity facets can be found in Appendix K. Correlations of survey items to persona lity facets were gene rally stronger than with survey items to teachi ng styles, with 74% of the it ems having higher correlations than .70 (highest was .92). Twenty-three it ems (19%) had correlations between .60 and .69, and only 8 of the 120 items (7%) had corr elations below .60; th e lowest one being .52. Reliability was also calculated on the cr iterion variables of concert and marching band ratings, FMBC competitive marching ratings, and ratings at state FBA concert band festival, based on a three-year sample for each subject. This reliability information is presented in Table 9. Alpha reliabilities for band ratings are strong for all types except state FBA concert festival, which is below the expected st andard for reliability (.70). This may be a result of the small number of subjects who participated in state FBA concert festival ( n = 81), and often a three-year mean was not avai lable since subjects in the sample attend state FBA concert festival a mean of only once every three years (as indicated in Table 3). This may also be a result of state FBA judges often being college band directors from other states who may have di fferent opinions as to what constitutes an ideal sound.
75 Table 8 Item to Personality Facet Correlati ons for the IPIP-NEO ________________________________________________________________________ Personality Facet Item 1 Item 2 Item 3 Item 4 ________________________________________________________________________ Neuroticism Anxiety .73 .77 .68 .78 Anger .86 .86 .87 .72 Depression .84 .78 .92 .73 Self Consciousness .78 .69 .78 .62* Immoderation .71 .62 .67 .72 Vulnerability .78 .83 .66 .70 Extraversion Friendliness .77 .87 .73 .80 Gregariousness .85 .78 .74 .87 Assertiveness .84 .74 .82 .77 Activity .59 .71 .71 .59 Excitement Seeking .63 .73 .67 .72 Cheerfulness .77 .70 .72 .81 Openness to Experience Imagination .54 .81 .85 .80 Artistic Interest .54 .54 .79 .77 Emotion .63 .54 .64 .63 Adventurousness .70 .78 .77 .76 Intellect .61* .75 .72 .80 Liberalism .91 .66 .89 .52 Agreeableness Trust .88 .78 .86 .88 Morality .83 .61 .78 .60 Altruism .74 .79 .67 .73 Cooperation .68 .77 .78 .69 Modesty .78 .83 .83 .59 Sympathy .80 .77 .65 .70 Conscientiousness Self Efficacy .76 .71 .74 .77 Orderliness .83 .83 .86 .80 Dutifulness .70 .68 .72* .68 Achievement Striving .77 .78 .75 .69 Self Discipline .73 .62 .83 .76 Cautiousness .84 .89 .88 .90 ________________________________________________________________________ *item was removed to improve reliability
76 Table 9 Reliability Data for Band Ratings __________________________________________ Band Ratings CronbachÂ’s __________________________________________ FBA Marching .83 FBA Concert .74 FMBC Marching Competitions .94 State FBA Concert .60 __________________________________________ Correlations were calculated for teac hing experience and academic degree with the criterion variables. Although academic degrees are not considered interval data, they are ordinal, with the code (3) representing Bachelors degrees, (4) representing Masters degrees, and (5) representing Specialist or incomplete Doctoral degrees. These correlations and are presented in Table 10. Table 10 Correlations for Criterion Variables with Experience and Academic Degree _______________________________________________________________ Criterion Variable Experience r ( n ) Degree r ( n ) _______________________________________________________________ Concert ratings .34 (165)*** .18 (165)* Marching ratings .20 (161)* .18 (161)* State Concert ratings .18 (80) .20 (80) State Concert attend. .11 (172) .11 (172) FMBC ratings .20 (123)* .11 (123) FMBC attend. -.09 (172) .06 (172) _______________________________________________________________ p < .05, ** p < .01, and *** p < .001
77 There are low but significant positive correlations for experience and concert ratings ( r = .34, p < .001), marching ratings ( r = .20, p < .05), and FMBC ratings ( r = .20, p < .05). The table also indicates low but sign ificant correlations for education and concert ratings ( r = .18, p < .01), and marching ratings ( r = .18, p < .05). Predictor variables were correlated w ith the criterion variables and are presented in Table 11. Significant positive correlations exist between concert band ratings and the teaching styles Time Efficiency ( r = .39, p < .001), Music Concept Learning ( r = .30, p < .001), Artistic Musical Performance ( r = .24, p < .001), and Student Independence ( r = .21, p < .01). Significant positive correlations exist between marching band ratings and the teaching styles Assertive Teaching ( r = .16, p < .05), Time Efficiency ( r = .37, p < .001), and Music Concept Learning ( r = .27, p < .001). The four remaining criterion variables each had a significant positive co rrelation with Time Efficiency. All four correlations with Time Efficiency were rath er low, but all were significant: State FBA concert band ratings ( r = .25, p < .05), State FBA concert band festival attendance ( r = .22, p < .01), FMBC ratings ( r = .26, p < .01), and FMBC attendance ( r = .20, p < .01). It is noteworthy that Time Efficiency has a sign ificant relationship with all of the criterion variables. State concert band attendance also had a significant correlation with Music Concept Learning ( r = .18, p < .05). Significant positive correlations exist between several personality facets and criterion variables. Higher concert band ra tings are significantly positively correlated with Assertiveness ( r = .27; facet of Extraversion), Self-Efficacy ( r = .25; facet of Conscientiousness), Immoderation ( r = .19; facet of Neuroticism), and Achievement Striving ( r = .10; facet of Conscientiousness).
78 Table 11 Correlations for Criterion Variables and Pr edictor Variables (n in parentheses) ________________________________________________________________________ Dimension Concert Marching SCB Ratin g SCB Attend CM Rating CM Attend ________________________________________________________________________________________________ Teaching Style Assertive Teaching .10 (165) .16 (163)* .02 (81) -.03 (175) .05 (124) .02 (175) Nonverbal Motivation .11 (165) .13 (163) -.01 (81) .03 (175) .04 (124) -.04 (175) Time Efficiency .39 (165)*** .37 (163)*** .25 (81)* .26 (175)*** .26 (124)** .20 (175)** Positive Learning Environ. .11 (165) .03 (163) -.08 (81) -.04 (175) .01 (124) .00 (175) Group Dynamic .14 (165) .04 (163) -.17 (81) -.03 (175) -.08 (124) .02 (175) Music Concept Learning .30 (165)*** .27 (163)*** .03 (81) .18 (175)* .14 (124) -.02 (175) Artistic Music Perform. .24 (165)** .12 (163) .14 (81) .10 (175) .04 (124) -.05 (175) Student Independence .21 (165)** .12 (163) .02 (81) .11 (175) .07 (124) .04 (175) Neuroticism Anxiety -.04 (147) -.07 (145) .17 (71) .02 (156) .04 (110) -.03 (156) Anger .04 (146) -.06 (144) .09 (71) .15 (155) .15 (109) .08 (155) Depression -.03 (146) -.03 (144) .09 (71) .02 (155) .01 (109) -.08 (155) Self Consciousness .04 (146) -.05 (144) .07 (71) .12 (155) .16 (109) .10 (155) Immoderation .19 (145)* -.02 (143) -.17 (71) .20 (154)* -.03 (108) .08 (154) Vulnerability -.09 (145) -.08 (143) .05 (71) .01 (154) .01 (108) .03 (154) Extraversion Friendliness .11 (147) .13 (145) .02 (71) .01 (156) -.01 (110) .04 (156) Gregariousness .10 (146) .09 (144) .07 (71) -.01 (155) -.06 (109) -.05 (155) Assertiveness .27 (145) ** .13 (143) .09 (71) .19 (154) -.01 (108) .06 (154) Activity .12 (145) .19 (143) .09 (71) -.01 (154) .17 (108) .18 (154) Excitement Seeking .13 (145) .08 (143) -.15 (71) -.04 (154) .12 (108) .16 (154) Cheerfulness .03 (145) .05 (143) -.10 (71) -.10 (154) -.07 (108) -.06 (154) Openness to Experience Imagination .01 (147) -.16 (145) -.18 (71) -.05 (156) -.07 (110) -.07 (156) Artistic Interest .04 (146) .01 (144) -.18 (71) .02 (155) -.13 (109) -.01 (155) Emotion .07 (145) .00 (143) .08 (71) -.01 (154) -.09 (108) -.17 (154) Adventurousness .05 (145) .05 (143) -.08 (71) -.03 (154) .08 (108) .10 (154) Intellect .14 (145) .07 (143) -.08 (71) .07 (154) .00 (108) .12 (154) Liberalism .01 (145) .06 (143) -.21 (71) -.01 (154) .00 (108) .11 (154) Agreeableness Trust .12 (147) -.02 (145) .12 (71) .00 (156) .11 (110) .05 (156) Morality -.09 (146) -.04 (144) .07 (71) -.10 (155) .00 (109) -.08 (155) Altruism .00 (145) -.09 (143) -.12 (71) -.09 (154) -.17 (108) -.10 (154) Cooperation .08 (145) .03 (143) .05 (71) .04 (154) -.13 (108) -.17 (154) Modesty .01 (145) -.12 (143) .13 (71) -.16 (154) -.11 (108) -.18 (154) Sympathy .06 (145) -.01 (143) -.17 (71) -.14 (154) -.13 (108) -.04 (154) Conscientiousness Self Efficacy .25 (147)** .23 (145) ** .03 (71) .17 (156)* .10 (110) -.01 (156) Orderliness -.04 (146) .05 (144) -.11 (71) -.11 (155) -.17 (109) -.06 (155) Dutifulness .01 (145) -.05 (143) .07 (71) -.04 (154) -.16 (108) -.16 (154)* Achievement Striving .10 (145)* .09 (143) -.01 (71) .04 (154) .12 (108) -.01 (154) Self Discipline .10 (145) .14 (143) -.10 (71) -.07 (154) -.03 (108) .03 (154) Cautiousness -.07 (145) .07 (143) .04 (71) -.12 (154) -.10 (108) -.15 (154) SCBState Concert Band, CMFMBC Competitive Marching Band *significant at p < .05, **significant at p < .01, ***significant at p < .001
79 Higher marching band ratings are significantly positively correlated with Activity ( r = .19; facet of Extraversion) and Self-Efficacy ( r = .23; facet of Conscientiousness). There are four personality facets which have si gnificant correlations w ith participation in FMBC competitive marching band events. Emotion ( r = -.17; facet of Openness to Experience), cooperation and modesty ( r = .17 and -.18, respectively; facets of Agreeableness), and dutifulness ( r = -.16; facet of Conscienti ousness) all show significant negative correlations with participation in FMBC competitive marching band events. That is, participation in these competitive marching band events correspond with a decrease in emotion, cooperation, modest y, and dutifulness. The facet activity ( r = .18; facet of Extraversion) has a positive co rrelation with FMBC competitive marching band events. Two personality facets correlate signifi cantly with participat ion in state concert band attendance; Immoderation ( r = .20; facet of Neuroticism), Self Efficacy ( r = .17; facet of Conscientiousne ss) and Assertiveness ( r = .19; facet of Extraversion). As recommended by Gumm, it may be important in teaching style research to determine the interaction of personality and teaching styl e. Correlations between teaching styles and personality facets are presented in Table 12. There are some noteworthy correlations be tween teaching styles and personality facets. The strongest correlations were between Altruism and Positive Learning Environment ( r = .46, p < .001), and between Self Efficacy and Time Efficiency ( r = .41, p < .001). Four other significan t correlations are worth no ting: Self Discipline with Student Independence ( r = .39, p < .001), Morality with Posi tive Learning Environment ( r = .35, p < .001), Cheerfulness with Nonverbal Motivation ( r = .35, p < .001), and Activity with Time Efficiency ( r = .34, p < .001).
80 Table 12 Correlations Between Teaching Styl es and Personality Facets ________________________________________________________________________ Personality Facet AT NM TE PLE GD MCL AMP SI ________________________________________________________________________ Neuroticism Anxiety .11 -.08 .02 -.11 -.05 .04 -.09 -.05 Anger .15 .02 .06 -.16 -.07 -.01 -.01 -.02 Depression -.08 -.12 -.10 -.17* .00 .01 -.13 -.11 Self Consciousness .17* .04 .09 -.13 -.05 .01 .01 -.01 Immoderation -.06 .00 .03 -.11 -.01 -.02 -.12 -.06 Vulnerability .01 -.10 -.08 -.12 -.09 -.04 -.14 -.17* Extraversion Friendliness .15 .25** .12 .20* .16* .22** .25** .27** Gregariousness .19* .27** .11 .14 .18* .20* .20* .18* Assertiveness .15 .23** .28*** -.01 .18* .11 .20* .22** Activity .18* .19* .34*** .11 .31*** .17* .14 .20* Excitement Seeking .00 .26** .20* .10 .21** .17* .15 .11 Cheerfulness .09 .35*** .29*** .32*** .21** .14 .22** .19** Openness to Experience Imagination -.03 .14 .02 -.08 .08 .02 .12 .02 Artistic Interest .00 .26** .18* .15 .19* .18* .28*** .25** Emotion .01 .31*** .10 .22** .14 .14 .22** .24** Adventurousness -.06 .15 .05 .11 .25** .12 .10 .15 Intellect -.03 .15 .05 -.06 .10 .11 .17* .19* Liberalism -.06 .09 .11 -.05 -.01 -.05 -.05 .00 Agreeableness Trust -.15 .03 .07 .14 .00 .01 .01 .00 Morality -.07 .00 .07 .35*** .21** .13 .07 .18* Altruism .05 .23** .12 .46*** .20* .17* .20* .30*** Cooperation -.09 .03 .08 .30*** .14 .09 -.06 .02 Modesty -.02 -.20* -.05 .14 .08 .08 .01 .12 Sympathy .06 .11 .04 .17* .09 .07 .05 .06 Conscientiousness Self Efficacy .21** .29*** .41*** .21** .19* .26** .26** .28*** Orderliness .12 .08 .04 .11 .19 .10 .02 .05 Dutifulness -.05 .06 .13 .20* .15 .02 .11 .07 Achievement Striv. .07 .18* .27** .26** .25** .24** .18* .28** Self Discipline .16* .31*** .27** .29*** .32*** .26** .30*** .39*** Cautiousness -.01 -.08 .03 .16* .02 .01 .01 .00 ________________________________________________________________________ N = 155, p > .05 ** p > .01, *** p > .001
81 The Research Questions To answer the first two questions, Â“What kinds of relationships exist between band directorsÂ’ personality types or teaching st yles and their concert band ratings?Â” and Â“What kinds of relationships ex ist between band directorsÂ’ pe rsonality types or teaching styles and their marching band ratings?Â” the data were analyzed using multiple regression for the thirty-eight predictor variables of personality (anx iety, anger, depression, self consciousness, immoderation, vulnerability, frie ndliness, gregariousne ss, assertiveness, activity, excitement seeking, cheerfulness, imagination, artistic interest, emotion, adventurousness, intellect, liberalism, trus t, morality, altruism, cooperation, modesty, sympathy, self efficacy, orderliness, dutifulness, achievement striving, self discipline, and cautiousness) and eight teaching styles (ass ertive teaching, nonverbal motivation, time efficiency, positive learning environmen t, group dynamics, music concept learning, artistic music performance, and student i ndependence), on the crit erion variables of marching ratings and concert ratings. To address the first research question, I used stepwise multiple regression with concert ratings as the criterion variable and th e thirty-eight predictor variables in teaching style and personality as pred ictor variables. SPSS calculated which variables to include with the criteria probability of F to enter .05, probability of F to remove .10. I then repeated the regression procedure above excep t with marching ratings as the criterion variable. Table 13 displays a summary of the stepwise regression procedures.
82 Table 13 Stepwise Regression and ANOVA for B and Ratings and Predictor Variables ________________________________________________________________________ Step Predictor Variables Included R R2 adj R2 df F p < ________________________________________________________________________ Concert Band ratings 1 Time Efficiency (TE) .37 .13 .13 1, 143 21.99 .001 2 TE, Immoderation (I) .41 .17 .16 2, 142 14.52 .001 3 TE, I, Music Concept Learn. (MCL) .44 .20 .18 3, 141 11.51 .001 4 TE, I, MCL, Assertiveness (A) .47 .22 .20 4, 140 10.07 .001 5 TE, I, MCL, A, Nonverbal Motiv. .50 .25 .23 5, 139 9.47 .001 Marching Band ratings 1 Time Efficiency (TE) .35 .12 .12 1, 141 18.69 .001 2 TE, Imagination (Im) .38 .15 .14 2, 140 12.10 .001 3 TE, Im, Modesty (M) .42 .17 .16 3, 139 9.75 .001 4 TE, Im, M, Cheerfulness (C) .45 .20 .18 4, 138 8.75 .001 5 TE, Im, M, C, Anxiety (Anx) .48 .23 .20 5, 137 8.20 .001 6 TE, Im, M, C, Anx + MCL .50 .25 .22 6, 136 7.67 .001 ________________________________________________________________________ Using concert band ratings as the criterion variable, SPSS entered Time Efficiency in the first step. The second step included both Time Efficiency and Immoderation, while the third step added to these two predic tors Music Concept Learning, the fourth step adde d Assertiveness, and the fift h and final step included the previous four predictors al ong with Nonverbal Motivation. Th e final step containing the five predictors is considered significant: F (5, 139) = 9.47, p < .001, and accounts for approximately 23% of the variation in concert band ratings (adjusted R2 = .23). SPSS did not include any other predicto rs in the stepwise regressi on for concert band ratings as they were determined not to contribut e significantly to their variation.
83 Using marching band ratings as the cr iterion variable, SPSS entered Time Efficiency in the first step. The second step included both Time Efficiency and Imagination, while the third st ep added Modesty to these two predictors. The fourth step added Cheerfulness, the fifth step added A nxiety, and the sixth and final step added Music Concept Learning to the previous five predictors. The final st ep containing the six predictors is considered significant: F (6, 136) = 7.67, p < .001, and accounts for approximately 22% of the variation in concert band ratings (adjusted R2 = .22). SPSS did not include any other predictor variables in the stepwise regression for marching band ratings as they were determined not to contribute significantly to the variation in marching band ratings. Regression coefficients for each of th e predictor variables included in the stepwise regression procedure were calculated along with p values and tolerance for multicollinearity. All regression coefficients were significant at the .05 level, and most have a very high tolerance for multicollinearit y. The lowest two tolerance values were .68 for Time Efficiency as a pred ictor of concert band ratings and .65 for Cheerfulness as a predictor of marching band ratings. Table 14 provides regression coefficients for the predictor variables in each of the steps in the regression. Although I used linear multiple regression to examine teaching styles and personality facets on the criterion variables, the data were also examined using nonlinear regression methods including logarithmic, quadratic, inverse, cubic, and compound methods to determine if there were any curv ilinear or other nonlin ear relationships. No significant relationships were detected using these nonlinear regression methods.
84 Table 14 Regression Coefficients for Predictor Variabl es associated with Criterion Variables ________________________________________________________________________ Predictors included B SE B t p < tolerance ________________________________________________________________________ Concert Band ratings Time Efficiency .40 .12 .30 3.35 .001 .68 Immoderation .15 .06 .19 2.58 .05 .99 Music Concept Learning .26 .09 .23 2.83 .01 .74 Assertiveness .20 .07 .25 2.49 .05 .91 Nonverbal Motivation -.27 .12 -.21 -2.39 .05 .72 Marching Band ratings Time Efficiency .42 .10 .37 4.30 .001 .76 Imagination -.12 .05 -.20 -2.51 .05 .91 Modesty -.11 .05 -.19 -2.35 .05 .88 Cheerfulness -.26 .08 -.31 -3.33 .001 .65 Anxiety -.13 .06 -.21 -2.38 .05 .70 Music Concept Learning .19 .09 .17 2.02 .05 .81 _______________________________________________________________________ To answer the third and fourth ques tions, Â“In what ways do band directorsÂ’ personality types or teaching st yles contribute to the number of state concert band events in which their bands participated?Â” and Â“I n what ways do band di rectorsÂ’ personality types or teaching styles contribute to the number of competitive marching band events in which their bands participated?Â” I used stepwi se multiple regression with the thirty eight predictor variables and the cr iterion variables of state FB A concert festival attendance and FMBC competitive marching band event attendance. Results of these regression procedures are indicated in Table 15.
85 Table 15 Stepwise Regression and ANOVA for Stat e Concert Attendance and FMBC Attendance ________________________________________________________________________ Step Predictor Variables Included R R2 adj R2 df F p < ________________________________________________________________________ State FBA Concert Band Attendance 1 Time Efficiency (TE) .24 .06 .05 1, 152 9.11 .01 2 TE + Pos. Learn. Environ (PLE) .31 .10 .09 2, 151 8.17 .001 3 TE + PLE + Immoderation (Im) .36 .13 .11 3, 150 7.31 .001 4 TE + PLE + Im + MCL* .40 .16 .13 4, 149 6.87 .001 5 TE + PLE + Im + MCL + GD* .45 .20 .17 5, 148 7.44 .001 6 TE + PLE + Im + MCL + GD + AT* .48 .23 .20 6, 147 7.27 .001 FMBC Competitive Marching Band Attendance 1 Time Efficiency (TE) .19 .04 .03 1, 152 5.68 .05 2 TE + Dutifulness (D) .27 .07 .06 2, 151 5.92 .01 3 TE + D + Nonverbal Motiv. (NM) .32 .10 .08 3, 150 5.69 .001 4 TE + D + NM + Modesty .37 .14 .11 4, 149 5.87 .001 ________________________________________________________________________ *MCLMusic Concept Learning, GDGroup Dynamic ATAssertive Teaching Using state FBA concert band attendance as the criterion variable, SPSS entered Time Efficiency in the first step. The sec ond step included both Time Efficiency and Positive Learning Environment, while the th ird step added to these two predictors Immoderation. Step four added Music C oncept Learning, step five added Group Dynamic, and the sixth and final model include d the previous five predictors along with Assertive Teaching. The final st ep containing the six predicto rs is considered significant: F (6, 147) = 7.27, p < .001, and accounts for approximately 20% of the variation in state FBA concert band festival attendance (adjusted R2 = .20). SPSS did not include any other
86 predictor variables in the stepwise regressi on for state concert band attendance as they were determined not to contri bute significantly to the vari ation in concert band ratings. Using FMBC competitive marching band at tendance as the criterion variable, SPSS entered Time Efficiency in the first step. The second step included both Time Efficiency and Dutifulness, while the third st ep added Nonverbal Mo tivation to these two predictors. The fourth and final step added M odesty to the previous three predictors. The final step containing the four pred ictors is considered significant: F (4, 149) = 5.87, p < .001, and accounts for approximately 11% of the variation in concert band ratings (adjusted R2 = .11). SPSS did not include any other pr edictor variables in the stepwise regression for FMBC competitive marching band attendance as they were determined not to contribute significantly to the vari ation in FMBC competitive marching band attendance. Regression coefficients for each of th e predictor variables included in the stepwise regression procedure were calculated along with p values and tolerance for multicollinearity. All regression coefficients were significant at the .05 level, and most have a very high tolerance for multicollinear ity. The only two tolerance values below .70 were Group Dynamic (.63) and Music Concept L earning (.56) as predic tors for state FBA concert band attendance. Table 16 provides regression coefficients for the predictor variables in each of the steps in the regression. To address the fifth research questio n, Â“In what ways do band directorsÂ’ personality types or teaching styles contribute to the balance between marching and concert band participation and scores?Â” I fi rst generated frequenc ies and descriptive statistics for the variable ba lance, which indicated 83.4% ( n = 131) of subjects were
87 Table 16 Regression Coefficients for Predictor Variabl es associated with Criterion Variables ____________________________________________________________________ Predictors included B SE B t p < tolerance ____________________________________________________________________ State FBA Concert Band Attendance Time Efficiency .31 .08 .36 4.07 .001 .70 Positive Learning Environ. -.19 .07 -.23 -2.63 .01 .70 Immoderation .09 .04 .16 2.24 .05 .98 Music Concept Learning .30 .08 .36 3.71 .001 .56 Group Dynamic -.21 .07 -.27 -2.97 .01 .63 Assertive Teaching -.14 .06 -.19 -2.31 .05 .81 FMBC Competitive Marching Band Attendance Time Efficiency .91 .25 .32 3.63 .001 .77 Dutifulness -.46 .20 -.17 -2.25 .05 .97 Nonverbal Motivation -.67 .25 -.24 -2.71 .01 .74 Modesty -.29 .12 -.19 -2.42 .05 .94 ____________________________________________________________________ Table 17 Descriptive Statistics of Crite rion Variables by Balance ________________________________________________________________________ Balanced Marching-Oriented Variable n M SD skew. kurt. n M SD skew. kurt. ________________________________________________________________________ Marching 131 1.44 .49 1.18 .90 26 1.37 .36 .57 -.96 Concert 131 1.62 .50 1.43 2.84 26 2.29 .36 .06 -.80 FMBC score 94 72.08 9.88 -.08 -1.05 26 71.98 8.20 -.22 -.74 FMBC attend. 131 1.23 1.20 .72 -.61 26 2.53 1.31 .00 -1.38 ________________________________________________________________________
88 balanced, and 16.6% ( n = 26) were marching oriented. No pa rticipants were classified as concert-oriented. Frequencies and percentage s for balance by gender, academic degree, and instrument are located in Appendices G, H, and I. Descriptive statistics for the criterion variables based on ba lance classification are listed in Table 17. No information is provided for state concert band ratings or participation since by definition no marching oriented subjects particip ated in these events. Although the two groups have very si milar means for marching band ratings, there is slightly more variability in the m ean ratings of balanced subjects. Balanced subjects scored a mean of .67 points higher than marching-oriented subjects on concert band ratings. The marching category was defi ned as having a concert rating a minimum of .50 points Â“lowerÂ” (closer to 1.00; a Superior ) than their marching rating, but the data reveal marching-oriented subjects had a m ean concert score .92 poi nts lower than their mean marching ratings. The mean for FMBC competitive marching band events was actually .10 points lower for ma rching-oriented subjects ( M =71.98) than balanced subjects ( M =72.08). Marching-oriented subjects a ttended a mean of 2.53 FMBC events annually, more than twice as often as bala nced subjects who atte nded a mean of 1.23 annually (a difference of 1.30 events per year). To establish a clearer picture of the differences between the balanced and marching-oriented groups in relation to the criterion variables, a MANOVA was computed using the criterion variables of marching and concert band scores as well as frequency of attending marching competitions and state concert band fe stival. Prior to the MANOVA, the BoxÂ’s M test of homogeneity of variance was 7.86 ( F = .74, p > .05), non-significant, indicating the homogeneity of variance assumption was met. The
89 MANOVA result indicated a significant diffe rence between the tw o groups, with a WilksÂ’ = .46, F =33.33, p < .001. There was a medium effect size (partial 2 = .54) and a strong observed power of 1.00. The Univariate F tests (see Table 18) indicated there was no significant difference between the bala nced and marching oriented subjects in their mean marching band scores: F (1, 118) = .00, p > .05. Concert band ratings were significantly higher for balanced subject s than marching-oriented subjects: F (1, 118) = 63.82, p < .001. The difference in FMBC scores betw een balanced and marching-oriented subjects is not significant: F (1, 118) = .00, p > .05. The finding that marching-oriented subjects attended a mean of mo re than twice as many FMBC events as balanced subjects annually was a significant difference: F (1, 118) = 10.36, p < .01. Again, data for state concert band were not included since by de finition of the marching-oriented balance category, no subjects in this category participated in state concert band events. Table 18 Univariate F-tests of Criterion Variables on Balance ____________________________________________________________ Variable SS df F p ____________________________________________________________ Marching .00 1, 118 .00 >.05 Concert 10.34 1, 118 63.82 <.001 FMBC score .23 1, 118 .00 >.05 FMBC attend. 13.22 1, 118 10.36 <.01 ____________________________________________________________
90 Next I examine the effect of predictor variables of personali ty (anxiety, anger, depression, self consciousness, immoderation, vulnerability, fr iendliness, gregariousness, assertiveness, activity, excite ment seeking, cheerfulness, im agination, artistic interest, emotion, adventurousness, inte llect, liberalism, trust, morality, altruism, cooperation, modesty, sympathy, self efficacy, orderliness, dutifulness, achievement striving, self discipline, and cautiousness) and teachi ng styles (assertive teaching, nonverbal motivation, time efficiency, positive l earning environment, group dynamics, music concept learning, artistic music performance, and student independence) on the criterion variable of balance. Descri ptive statistics comparing the two groups is in Table 19. I then conducted a discriminant analysis with balance as the criterion variable, and the eight teaching style and thirty persona lity facets were the predictor variables. A total of 137 cases (77.8% of the total samp le) contained enough data to be analyzed. Results of the univariate ANOVA tests of equality generated by the discriminant procedure are presented in Table 20. The result s indicate only four pr edictor variables are significantly different betw een balanced and marching-oriented groups: Anxiety, Assertiveness, Emotion, and Adventurousness. The discriminant analysis procedure wh ich displayed the differences between means on predictor variables for balanced a nd marching oriented subjects revealed that they significantly differ on four pe rsonality facets. Anxiety (WilksÂ’ = .97, F [1, 135] = 4.11, p < .05), Assertiveness (WilksÂ’ = .96, F [1, 135] = 5.56, p < .05) and Adventurousness (WilksÂ’ = .96, F [1, 135] = 6.42, p < .05) and Emotion (WilksÂ’ = .97, F [1, 135] = 3.93, p < .05), and had significant effect s on discriminating between balanced subjects and marc hing oriented subjects.
91 Table 19 Descriptive Statistics of Predic tor Variables by Balance ________________________________________________________________________ Balanced Marching-Oriented Variable n M SD skew. kurt. n M SD skew. kurt. ______________________________________________________________________________________ Teaching Style Assert. Teach. 132 4.01 .53 -.23 -.44 26 3.98 .50 .22 -.46 Nonv. Motiv. 132 3.91 .49 -.08 .00 26 3.75 .34 -.31 -.29 Time Effic. 132 4.25 .48 -.42 -.66 26 4.10 .38 -.12 1.28 Pos. Lrn. Env. 132 4.22 .49 -.56 -.03 26 4.11 .42 .50 .03 Group Dynam. 132 3.27 .54 .14 .05 26 3.24 .46 -.71 .79 Mus. Conc. L. 132 3.78 .49 -.38 .48 26 3.64 .44 .50 -1.07 Art. Mus. Perf. 132 3.55 .51 -.42 .56 26 3.36 .59 .41 .02 Stud. Indep. 132 3.45 .59 .01 .06 26 3.32 .69 .66 -.35 PersonalityNeuroticism Anxiety 116 2.90 .83 .01 -.75 24 2.63 .83 .85 1.73 Anger 116 3.08 .94 -.26 -.53 23 2.82 .81 .10 -1.34 Depression 116 2.09 .85 .63 -.06 23 1.84 .56 .05 -1.00 Self Consc. 116 3.03 1.04 -.18 -.77 23 2.76 .87 .13 -1.15 Immoderation 115 2.87 .74 -.07 .41 23 2.56 .64 .36 -.39 Vulnerability 115 2.31 .84 .31 -.52 23 2.15 .71 .29 -.16 PersonalityExtraversion Friendliness 116 3.81 .78 -.53 -.45 24 3.90 .74 -.34 -.56 Gregariousness 116 2.98 1.00 -.06 -.96 23 3.07 .92 .17 -.52 Assertiveness 115 4.25 .63 -1.37 3.31 23 3.90 .59 -1.04 1.78 Activity 115 3.63 .68 -.16 -.55 23 3.68 .61 -.25 .00 Excite. Seek. 115 2.96 .72 .18 -.42 23 2.95 .52 .20 -.28 Cheerfulness 115 3.90 .63 -.23 -.66 23 3.98 .55 -.60 .64 PersonalityOpenness to Experience Imagination 116 3.46 .84 -.12 -.54 24 3.63 .84 .27 -.92 Artistic Int. 116 4.00 .67 -.90 1.08 23 4.18 .54 -.30 -.52 Emotion 115 3.80 .59 -.23 -.29 23 3.53 .56 -.53 -.76 Adventurous. 115 2.88 .82 .12 -.42 23 3.35 .73 .56 .29 Intellect 115 4.06 .83 -.67 -.30 23 4.12 .73 -.42 -.09 Liberalism 115 2.50 .96 .14 -.84 23 2.38 .96 -.24 -1.47 PersonalityAgreeableness Trust 116 3.62 .78 -.65 -.10 24 3.70 .87 -1.16 1.78 Morality 116 4.33 .62 -1.02 .93 23 4.34 .55 -.34 -1.13 Altruism 115 4.25 .59 -.76 .39 23 4.28 .40 .51 -.75 Cooperation 115 3.84 .86 -.70 .06 23 3.73 .74 .09 -.32 Modesty 115 3.12 .86 .12 -.91 23 3.08 .73 .60 -.85 Sympathy 115 3.68 .71 -.70 .91 23 3.84 .62 -1.00 2.56 PersonalityConscientiousness Self Efficacy 116 4.30 .49 -.57 -.15 24 4.19 .44 .19 -.56 Orderliness 116 3.47 1.05 -.34 -.83 23 3.33 .88 .00 -.93 Dutifulness 115 4.47 .50 -.57 -.57 23 4.52 .46 -.65 .32 Achieve. Striv. 115 4.61 .45 -1.02 .22 23 4.50 .46 -.41 -1.17 Self Discipline 115 3.86 .67 -.29 -.89 23 3.85 .58 -.22 -.07 Cautiousness 115 3.78 .96 -.64 -.29 23 3.84 .73 -.63 -.57 _____________________________________________________________________________________
92 Table 20 Difference of Group Means Between Balanced and Marching Oriented Subjects ________________________________________________________________________ Predictor WilksÂ’ F df p ______________________________________________________________________________________ Teaching Style Assertive Teaching 1.00 .01 1, 135 NS Nonverbal Motivation .99 1.93 1, 135 NS Time Efficiency .98 2.17 1, 135 NS Positive Learning Environment 1.00 .41 1, 135 NS Group Dynamic 1.00 .10 1, 135 NS Music Concept Learning .98 2.50 1, 135 NS Artistic Musical Performance .98 2.65 1, 135 NS Student Independence .99 1.07 1, 135 NS PersonalityNeuroticism Anxiety .97 4.11 1, 135 < .05 Anger .99 1.69 1, 135 NS Depression .99 1.82 1, 135 NS Self Consciousness .99 1.52 1, 135 NS Immoderation .97 3.68 1, 135 NS Vulnerability 1.00 .72 1, 135 NS PersonalityExtraversion Friendliness 1.00 .05 1, 135 NS Gregariousness 1.00 .15 1, 135 NS Assertiveness .96 5.56 1, 135 < .05 Activity 1.00 .07 1, 135 NS Excitement Seeking 1.00 .00 1, 135 NS Cheerfulness 1.00 .34 1, 135 NS PersonalityOpenness to Experience Imagination 1.00 .31 1, 135 NS Artistic Interest .99 1.41 1, 135 NS Emotion .97 3.93 1, 135 < .05 Adventurousness .96 6.42 1, 135 < .05 Intellect 1.00 .09 1, 135 NS Liberalism 1.00 .35 1, 135 NS PersonalityAgreeableness Trust 1.00 .01 1, 135 NS Morality 1.00 .01 1, 135 NS Altruism 1.00 .09 1, 135 NS Cooperation 1.00 .33 1, 135 NS Modesty 1.00 .06 1, 135 NS Sympathy .99 1.08 1, 135 NS PersonalityConscientiousness Self Efficacy .99 1.99 1, 135 NS Orderliness 1.00 .27 1, 135 NS Dutifulness 1.00 .13 1, 135 NS Achievement Striving .99 .93 1, 135 NS Self Discipline 1.00 .00 1, 135 NS Cautiousness 1.00 .08 1, 135 NS ________________________________________________________________________
93 A discriminant function was run using a ll predictor variables with a stepwise selection procedure, which used the probability of F (entry: .05, removal .10) method to determine inclusion in the discriminant function. Four steps were produced by SPSS, beginning with Adventurousness, followed by Adventurousness plus A ssertiveness, then the previous two plus Immoderation, and fi nally the preceding three predictors plus Emotion. This discriminant function was sable to significantly differe ntiate the variance between groups (WilksÂ’ = .84, 2 = 23.42, df = 4, p <.001). These resu lts are presented in Table 21. Table 21 Discriminant Function Analysis of Balance (Stepwise Entry Method) _________________________________________________________ Statistic Function _________________________________________________________ Eigenvalue .193 % of variance 100.0% Canonical correlation .402 WilksÂ’ .839 2 23.417 df 4 p < .001 Group centroid: Balanced .191 Group centroid: Marching-oriented -.996 _________________________________________________________ The discriminant function using the pred ictors Adventurousness, Assertiveness, Immoderation, and Emotion was able to succ essfully predict group membership 72.3% of the time. Prediction for membership in the ba lanced category is based on higher levels of
94 Assertiveness, Immoderation, and Emotion, a nd lower levels of Adventurousness, while the opposite predicts membership in the ma rching-oriented group. The function correctly predicted balanced subjects 73.0% of the time and correctly predicted marching-oriented subjects 68.2% of the time.
95 Chapter 5: Summary, Discussion, Conclusi ons, Implications, and Recommendations This chapter begins with a summar y of the study including the problem, theoretical framework, purpos e, research ques tions, literature review, methodology, and results of the data analysis. Following these are a discussion of the results, conclusions, and implications of this research for the field of music education. The final section includes recommendations for furthe r research in mu sic education. Summary The purpose of this research was to exam ine the relationship between high school band directorsÂ’ teaching style and personality and the directorÂ’s ratings in marching and concert band festivals. Personality was examined using the Fi ve-Factor model of personality which consists of five personality domains and thirty personality facets, and teaching style was examined using GummÂ’s Music Teaching Style Inventory which examined eight different modes of in struction. Band performance success was represented by concert and ma rching festival ratings. The literature indicated significant factors influencing band ratings such as school size, band size, budget, academic degree a nd teaching experience of band directors, having a higher percentage of juniors and se niors in the band, having a highly customized marching band show (both drill and music), ha ving larger numbers of assistant directors and staff members, attending a larger numb er of festivals and competitions, and studying concert band literature during marching band season. The literature on personality
96 focused primarily on Myers-Briggs personality types, and the most effective personality for a high school band director may be Intr overted, Intuitive, Th inking, and Judging, or INTJ (Mastermind). GummÂ’s model of teachi ng style has helped to better understand which teaching styles influence behavior and performance outcomes, and helped educators understand which styles they em ploy and to what degree. The research indicated the four student-directed teaching styl es are less prevalent than the four teacherdirected styles but may be indica tors of more effective teaching. This study was designed as a descriptive correlational st udy, with data gathered through an online survey and publicly availabl e band ratings on the internet. The entire population of 384 high school band directors in the state of Florida who directed both concert and marching band programs was offere d the survey. Criterion variables included marching and concert festival ratings, state concert band ratings, FMBC competitive marching band scores, frequency of attendance of these last two events, and the balance between marching and concert band. Predictor variables included thirty personality facets and eight teaching styles. Four demographic variables examined were gender, experience, highest academic degree, and primary instrument. Data collection resulted in 176 usable surveys (45.8% of the population). Time Efficiency stood out as having particularly st rong correlations with criterion variables. Regression models indicate 23% of the variation in concert band ratings can be predicted from five variables: Time Efficien cy, Immoderation, Music Concept Learning Assertiveness, and Nonverb al Motivation. For marching band scores, 22% of the variation in ratings can be e xplained by a set of six variab les: Time Efficiency, Music Concept Learning, Imagination, Modesty, Ch eerfulness, and Anxiety. Variation in
97 participation in state FBA concert band festiv al participation can be partially predicted with a combination of six predictor variab les: Time Efficiency, Positive Learning Environment, Immoderation, Music Concept Learning, Group Dynamic, and Assertive Teaching predict approximately 20% of the variation. Regression models found a combination of four variables which predict 11% of the variation in FMBC competitive marching band event: Time Efficiency, Nonverb al Motivation, Dutifulness, and Modesty. Most subjects (83.4%) were balanced in concert and marching band duties, while the remaining 16.6% were marching-oriented. Ba lanced and marching-oriented subjects differed significantly only on the criteri on variables of concert ratings and FMBC competitive marching band frequency. A discriminant function selected four predictor variables which had a significant effect: A ssertiveness, Immoderation, Adventurousness, and Emotion (WilksÂ’ = .84, 2 = 23.42, df = 4, p <.001). This function was able to successfully predict gr oup membership 72.3% of the time. Prediction for membership in the balanced category is based on higher leve ls of Assertiveness, Immoderation, Emotion, and lower levels of Adventurousness, while the opposite predicts membership in the marching-oriented group. Discussion The purpose of this research was to exam ine some of the relationships between high school band directorsÂ’ teaching style, pers onality and their ratings and attendance at marching and concert band festivals, as well as how band directors balance their responsibilities with marching and con cert bands. This study employed the Music Teaching Style Inventory, the Five-Factor model of personality, and published band ratings to address the research questions. Most reliability co efficients were sufficiently
98 high, between .70 and .85 for all three instrument s. The results are generalizable not only to Florida high school band di rectors (45.9% of the populatio n responded to the survey instrument, N =176), but due to the variety of types of communities represented across the state of Florida the results may also be gene ralized to other states where high school band directors are active in simila r activities of marching and concert band. This study only examines subjects in Florida in part since it is a relatively larg e and convenient sample which contains diverse communities. More importantly, keeping data from only one state helped to maintain consistencies with band ratings such as adjudication standards and rating systems. Reliability coefficients for al l data sources were generally moderate to high (mid-.60s to low .90s), with a few ex ceptions. The following discussion is organized to begin with the results of the preliminary analysis and descriptive data, followed by the research questions in order. The Preliminary Analysis Demographic variables provided some cont extual information about the subjects who participated in the study. As mentioned, the distribution of subjects by gender is a very accurate representation of the population, with 15.9% female and 84.1% male. Slightly more than half of the subjects indicated their highest degree was a Bachelors degrees (55.5%) while slightly less than half (42.2%) indi cated Masters degrees. Only four subjects (2.3%) indicated a Specialist or incomplete Doctoral degree. The distribution of subjectsÂ’ primary instru ments may be influenced by the gender distribution, as well as which instruments tend to be more common in band programs. Nearly 30% of the subjects played trumpet, followed by saxophone, trombone, percussion, and clarinet. The l east frequently chosen inst ruments were double reeds (5
99 bassoons and 1 oboe) which are the least used in struments in most bands, four flutes, all of whom were female (which represents less than 16% of the sample), and instruments which are not included in a typical band: pian o/keyboard (3) and stri nged instruments (1). Mean director experience was 12.77 years, although because of the number of lessexperienced directors there was a standard de viation of 9.94 years a nd the distribution is skewed positively (.93). The criterion variables indicated higher overall mean scores for marching band (1.45) than concert band (1.78). A possible reason for this may be that a school may only have one marching band, while it may have two, three, or sometimes even four concert bands, each receiving separate ratings (all bands in a school were averaged together for a given year in this study). While the shortc omings of weak musiciansÂ’ playing on a marching band field may be covered up by the so und of stronger players, this is not the case in smaller ensembles where students are often grouped by musical ability. Descriptive statistics for teaching styl es may be classified by teacher-directed styles (the first four: Assertive Teachi ng, Nonverbal Motivation, Time Efficiency, Positive Learning Environment) and student -director styles (the second four: Group Dynamics, Music Concept Learning, Artis tic Music Performance, and Student Independence). The teacher directed styles (means of 4.00, 3.89, 4.22, and 4.22, respectively) were all reported higher than a ll of the student-dire cted styles (3.27, 3.75, 3.53, and 3.43, respectively). This is similar to the results found by Bazan (2007) where middle school band directors reported a mean of 4.00 for teacher-dir ected styles and a mean of 3.08 for student-directed styles.
100 Most of the personality facets rema ined between 2.50 and 3.99, although eight personality facets were higher than 4.00. Three of these fell under the personality domain of Conscientiousness. The single highest personality facet was Achievement Striving ( M =4.61), followed closely by Dutifulness ( M =4.52) and Self Efficacy ( M =4.30). Two particularly high facets were part of the Agreeableness domain: Morality ( M =4.36) and Altruism ( M =4.26). One of the highest facets was part of the Extraversion domain: Assertiveness ( M =4.19), and the last two of the highe st rated facets were parts of the domain Openness to Experience: Intellect ( M =4.05) and Artistic Interest ( M =4.05). Two of the three lowest facets were parts of the Neuroticism domain: Depression ( M =2.04) and Vulnerability ( M =2.25), and one low facet, Liberalism ( M =2.48), is part of the Openness to Experience domain. Some facets indicated different findings than general population norms reported by Johnson (2005). Subjects scored lower on a ll facets of Neuroticism, especially on Depression (2.04 here versus 2.66 for norm). S ubjects scored higher on five of the six facets of Extraversion, although Gregarious ness was nearly the same (3.02 here compared to the norm of 3.00). The one Extrav ersion facet subjects sc ored lower in was Excitement Seeking (2.95 as opposed to th e norm 3.36). Openness to Experience had a mixture of higher facets and lo wer facets compared to the norms; two facets were higher (Artistic Interest was 4.05 instead of 3.89 and Intellect was 4.05 instead of 3.86) and four facets were lower. Subjects scored much lower than norms for Imagination (3.48 versus 4.01) and Liberalism (2.48 versus 2.98). For the domain of Agreeableness, subjects scored slightly above or very close be hind the population norms. Trust, Morality, Altruism, and Cooperation were above popul ation norms (by .35, .23, .18, and .17 points,
101 respectively) while Modesty and Sympathy we re slightly lower th an population (by .02 points and .03 points, respectively). The great est amount of difference was in the domain of Conscientiousness, where every facet wa s higher than the population norms, and typically by a large amount. The greatest di fference was with the facet of Achievement Striving, which was above pointed out as being the single highest facet for the subjects. The difference between subjects here and th e population norms is .75 points. The other facets were Cautiousness which was .62 point s higher, Self Discipline was .58 points higher, Dutifulness was .52 points higher, Orde rliness was .45 points higher, and Self Efficacy was .36 points higher. These findings indicate high school band dire ctors in this study have high levels of Conscientiousness and each of its facets. In fact, subjects indicated higher levels of every facet of Conscientiousness than populat ion norms. This may suggest the profession of high school band director may be attractiv e to people who are very conscientious, or being a high school band dire ctor develops conscientiousne ss in people. This may also suggest only conscientious high school band di rectors in the state of Florida completed the survey instrument. Along with being dedi cated, prudent, self-disciplined, responsible, organized, and generally competent, a typical high school band dire ctor in Florida may also be somewhat more outgoing, and more emotionally stable, down to earth, and politically conservative than me mbers of the general population. Correlations between academic degree a nd band ratings and between experience and band ratings support the findings of existing research. There is a small but significant correlation between subjectsÂ’ highest academic degree and band ratings ( r = .18, p < .05 for concert and r = .18, p < .05 for marching), which agrees with the findings of Beaver
102 (1973), Davis (2000), Dawes (1989), Fosse ( 1965), Goodstein (1984) Maxwell (1970), Mann (1979), Saul (1976), and Washington (2007) who also found a positive correlation between more advanced degrees and higherachieving bands. Researchers who indicated specific correlation coefficients produced co rrelations which were also relatively small yet significant. There is also a small but significant correla tion between subjectÂ’s experience and band ratings ( r = .34, p < .001 for concert ratings, r = .20, p < .05 for marching ratings, and r = .20, p < .05 for FMBC competitive marching ratings). This agrees with the findings of Davis (2000), Dawes (1989), DeCarbo (1986), Fosse (1965), Head (1983), Maxwell (1970), Mann (1979), Saul (1976), and Washington (2007) who also found festival ratings improve with in creased band director experience. As with academic degree, others found moderately low correlations similar to the findings here. Another finding in this study wh ich corresponds with existing research is that there is a small negative correlation (-.09, but non-significant) betwee n experience and attending FMBC competitive marching band events, which is similar to DawesÂ’ (1989) finding that less experienced and younger di rectors attended a larger num ber of competitions than older, more experienced directors. The correlation results indicate significan t positive correlations with concert band ratings and several teaching styles and pe rsonality facets including Time Efficiency, Music Concept Learning, Artistic Musica l Performance, Student Independence, Assertiveness, Self Efficacy, and Achiev ement Striving. There are also significant positive correlations for marching band ratings including Assertive Teaching, Time Efficiency, Music Concept Learning, Activ ity, and Self Efficacy. Time Efficiency, Assertiveness, and Self-Efficacy had signi ficant positive correlations with State FBA
103 concert band festival attendance. It is noteworthy that Time Efficiency had a significant positive correlation with all of the criterion variables. Time Efficiency was the only predictor variable with a significant positive correlation with ratings at FMBC competitive marching band events and state FBA concert ratings. Time Efficiency and Activity have significant positive correlations with attendance at FMBC competitive marching band events, and there are four personality facets with significant negative correlations as well: Emoti on, Cooperation, Modesty, and Du tifulness. This indicates those who attend fewer FMBC competitive ma rching band events indicated a tendency toward more emotion, a greater sense of cooperation, more modesty, and more dutifulness as measured by the IPIP-NEO. Research Question 1: What kinds of re lationships exist between band directorsÂ’ personality types or teaching styl es and their concert band ratings? The data suggest there are five pred ictor variables which have a strong relationship with concert band ratings. The combination of the teaching styles Time Efficiency, Music Concept Learning, a nd Nonverbal Motivation along with the personality facets Immoderation and Assertiv eness predict approximately 23% of the variation in concert band scores. These ag ree in part with the teaching styles Gumm (2003b) found to correlate to higher ratings for choral directors at contest, which were Artistic Music Performance and Nonve rbal Motivation. GummÂ’s (2003b) study incorporated other criteria such as highe st degree and geogra phical area along with teaching styles to determine factors which cont ributed to the variation in choral contest ratings. Artistic Music Performance and Nonve rbal Motivation along with highest degree and geographical area explained 34% of the variation in choral ratings. The fact that
104 personality facets and teaching styles only c ontributed 23% of the variance in criterion variables agrees with Washi ngtonÂ’s (2007) conclusions that factors pertaining to the students and the school contribute far more to a bandÂ’s success than aspects of the band director. Price (1983) and Yarbrough and Ma dsen (1998) found similar results with the predictor of Music Concept Learning influencing band ratings regarding teacher directions and class pacing. It is interesting that the stepwise re gression procedure indentified these five predictors to establish a model, which is ab le to indicate the most variation in concert band ratings and not others which were more strongly correlated. The procedure first included the strongest three correlated predictor variab les: Time Efficiency ( r = .33, p < .001), Music Concept Learning ( r = .30, p < .001), and Assertiveness ( r = .27, p < .01) but then the model did not include the next most strongly correlated predictors: Self Efficacy ( r = .25, p < .001), Artistic Music Performance ( r = .24, p < .01), and Student Independence ( r = .21, p < .01). However, the model then includes Immoderation ( r = .19, p < .05) and another teaching style which is not a significant correlation: Nonverbal Motivation ( r = .11, p > .05). Nonverbal Motivation is a negative predictor of concert band success: the beta coefficient indicates band ratings will decrease by .27 points for every 1 point of increase of Nonverbal Moti vation. The fact that Student Independence was not included confirms the findings of Petters (1976) who found student contribution to decisions on how to interpret music did not contribute significantl y to band ratings. These findings seem to indicate a strong leader who takes charge, uses every moment of rehearsal effectively, and is able to instruct the band effectively and teach musical concepts will be more effective in pr eparing a band for a performance. It may be
105 a director who is passionate and can b ecome emotionally involved with musical expression may also be prone to material i ndulgence, which may explain why there is a positive correlation between Immoderation and higher concert band ratings. Finally, as Nonverbal Motivation is a pr edictor of lower concert band ratings, it may be more important for directors in the concert ba nd setting to communicate more overtly and directly to be effective. Research Question 2: What kinds of re lationships exist between band directorsÂ’ personality types or teaching styl es and their marching band ratings? The data suggest there are six predictor variables which have a strong relationship with marching band ratings. The combination of the teaching styles Time Efficiency and Music Concept Learning and the personality facets Imagination, Modesty, Cheerfulness, and Anxiety predict approximately 22% of th e variation in marching band scores. Again, the teaching styles which influence the vari ation in marching band scores are different from the teaching styles than Gumm (2003b) found to correlate to higher ratings for choral directors at contest (Artistic Musi c Performance and Nonverbal Motivation). As with concert ratings the personality facets and teaching styles contributing only 22% of the variance in criterion variab les agrees with Washington Â’s (2007) conclusions that factors pertaining to the stude nts and the school contribute far more to a bandÂ’s success than aspects of the band director. It is also important to note there is a negative relationship with all four personality facets in th e regression model. The beta coefficients indicate marching band scores will tend to wards a lower rating by .12 points for every 1 point increase in Imagination, decrease .11 poi nts for every 1 point increase in Modesty, and decrease .26 points for ever y 1 point increase in Cheer fulness. While Imagination,
106 Modesty, and Cheerfulness may be considered by some as Â“positiveÂ” personality traits, there is also a negative correlation with one Â“negativeÂ” personality trait: Anxiety. The beta coefficient for Anxiety indicates marc hing band scores will tend toward a lower rating by .13 points for every point increase in Anxiety. Stated another way, marching band ratings improve with less anxious di rectors. Again the stepwise regression procedure used these six predictors to establis h a model which is able to indicate the most variation in marching band rati ngs but did not include all of the significantly correlated predictor variables. The pr ocedure included the two str ongest correlated predictor variables, Time Efficiency ( r = .37, p < .001), and Music Concept Learning ( r = .27, p < .001) but did not include Self Efficacy or Activity. As with concert band ratings, Music Con cept Learning appears to be a salient component of music education and rightly is part of the prediction model. Time EfficiencyÂ’s role in predicting success is an indication of the importance of accomplishing the numerous tasks associated with running an effective marching band program. Directors with high leve ls of Anxiety may not be able to successfully handle the numerous simultaneous responsibilities and activities involved in marching bands. Band directors who are level-headed and somb er of mood may be more prepared to successfully manage the direc tion and organization of the program which can result in emotional ups and downs with stress as well as performance success. Although Imagination may seem an important aspect of any creative art, the successful marching band director may hire drill wr iters and arrangers to take car e of the creative aspects of the marching band program while the director manages the task of teaching the music and drill routines. A humble or modest director may be less inclined to show off the bandÂ’s
107 talent, while the director with a sense of pride may showcase the band to its fullest potential. Research Question 3: In what ways do band directorsÂ’ personalit y types or teaching styles contribute to the number of stat e concert band events in which their bands participated? State FBA concert band festival particip ation appears to have a significant relationship with six predictor variables. Th e combination of the teaching styles Time Efficiency, Positive Learning Environment, Music Concept Learning, Group Dynamic, Assertive Teaching and the pers onality facet Immoderation pr edict approximately 20% of the variation in frequency of state FBA concer t band festival attendanc e. The influence of Group Dynamic is similar to GummÂ’s (2003b) finding that Group Dynamic, along with Artistic Music Performance, experience, geogr aphic location, and frequency of workshop training accounted for 31% of the variation in choral music fes tival participation. Increases in Time Effici ency, Music Concept Learni ng, and Immoderation predict increases in frequency of atte ndance at state FBA concert ba nd festival, while the other three predict decreases in attendance. Higher levels of Assertive Teaching, Group Dynamic, and Assertiveness correlated with less frequent attendance at state FBA concert band festival. Three of the five significantly co rrelated predictors were included in this model, but Self Efficacy and Assertiveness were not. To be able to participate in state concer t band festival the director must use every moment of rehearsal time effectively while be ing an effective music teacher. In order to use rehearsal time effectively the director ma y be less concerned with student input or delegation of responsibility to students. Ev en though this may help develop effective
108 student leaders, the learni ng process of students taking charge may slow down the process of driving towards the goal of perfec ting a piece of music. There is a negative relationship with Assertive Teaching, whic h is characterized by emphasis on following instructions and keeping discip line. It may be that the mo re successful directors have already established expectati ons of discipline ear lier in their career and it no longer needs to be addressed on a regular basis. Like concert band ratings, an increase in Immoderation corresponds with an increase in participation in state FBA concert band festival. The negative relation with Positive Learning Environment (PLE) may be related to the need for the director to dominate th e rehearsal with this very high level of performance achievement. Two-way interactions between director and students, careful and judicious use of praise, and positive reinforcement are some of the primary characteristics of PLE. The director who take s his or her band to state FBA more often may be more focused on rigorously correcting an d perfecting the music than with what he or she may conceive of as coddling studentsÂ’ feelings during rehearsals. Research Question 4: In what ways do band directorsÂ’ personalit y types or teaching styles contribute to the number of compe titive marching band events in which their bands participated? Variation in FMBC competitive marching ba nd event participati on is predicted by four variables in the stepwise regression m odel. The combination of the teaching styles Time Efficiency and Nonverbal Motivation wi th the personality facets Dutifulness and Modesty predict approximately 11% of the variation in frequency of FMBC competitive marching band event participati on. Increases in Time Effici ency predict increases in frequency of attendance FMBC competitive ma rching band events, wh ile the other three
109 predict decreases in attendance. Higher le vels of Dutifulness, Modesty, and Nonverbal Motivation are predicted to decrease frequency of attendance at FMBC competitive marching band events. Nonverbal Motivation is not significantly correlated with FMBC participation, but has been included in the model. Four personality facets which have significant correlations with FMBC participa tion were not included in the regression model, which are Activit y, Cooperation, and Emotion. Although personality and teaching style pr edict only 11% of the variation in participation in marching band competitions, those components that do influence it are similar to those indicators of success with marching band. The same reasons Time Efficiency and Modesty influence marching band seem to logically also influence participation in marching band competitions. Dutifulness is a predictor of less frequent participation in marching band competitions, wh ich may indicate it c ould be irresponsible for the director to overtax students by engaging them in marching competitions repeatedly during the marching season. Research Question 5: In what ways do band directorsÂ’ personalit y types or teaching styles contribute to the balance between marching and concert band participation and scores? Before examining the predictor variablesÂ’ effect on balance, I first determined the percent of the subjects who are in each category. Balanced subjects were 83.4% of the sample, and the other 16.6% were marching-or iented. No directors were classified as concert oriented. I then indicated descrip tive statistics for the criterion variables by balance category, and then dete rmined if the difference we re significant. There is no significant difference between balanced and ma rching-oriented subjects in achievement
110 at marching band events or FMBC competitive marching band events. That is, marchingoriented subjects are not significantly better th an balanced directors at the two things which define them: FBA marching ratings and competitive marching ratings. However, balanced directors score si gnificantly higher at concert band festival, and marching oriented directors attend FM BC competitive marching band events significantly more often than balanced directors. The disc riminant function incl uded four predictor variables: Assertiveness, Immoderation, Adventurousness, and Emotion. This discriminant function was able to significantly differentiate the variance between groups (WilksÂ’ = .84, 2 = 23.42, df = 4, p <.001). Since this variable of balance is an experimental construct and is not known to exist in any other literature, there is no available information with which to compare these results. Assertive leaders who take charge of th eir ensembles may be more likely to be balanced since the success at marching bands may be a result of several other staff members or instructors, eliminating the need fo r the director to be a ssertive, take charge, and be a leader. Directors who prefer trave ling and seeking new challenges may be more inclined to be more active with the marching band rather than focusing on the more consistent and stable indoor concert band wh ere artistic performance is more common than high-pressure competitions at district, state, or national leve ls. The most intriguing finding is that of Immodera tion. The findings with marchi ng band directors indicated they were perhaps more down to earth and somber, so this may be an indication that those who tend towards excess may be indi cative of a tendency to show a focus on concert band which balanced the marching ba nd. With less self-dis cipline a person might be more prone to partake in excesses. Th e same passion, which is a part of rich
111 enjoyment of beautiful sounds, may also lead towards enjoyment of rich foods, drink, or other indulgences. Emotional expression may be related to this Immoderation. Since music is a form of expression, it is natural that emotional e xpressiveness can be tied to this. There are typically more opportunities for expressiveness, rich emotion, and passionate involvement with concert band literature than with a field show. Some predictor variables are included in regression models for more than one criterion variable. Some of the predictors pred ict increases in the criterion variable, while others predict decreases. Table 22 provides a summary of the significant predictor variables which have been included in the regression models for research questions 1 through 4 as well as the discriminant functi on for research question 5. A positive sign (+) indicates the criterion variable is expected to increase with higher levels of the predictor variable, while a negative sign ( -) indicates the criterion variab le is expected to decrease with an increase in th e predictor variable. Conclusions Although the subjects for this study were ex clusively from the st ate of Florida, it may be fair to generalize the results to other states where similar concert and marching band events take place. Not only were response s received from each FBA district within the state covering a wide geographic distribut ion and a variety of community types, but the state of Florida is diverse in terms of socioeconomic stat us, ethnicity, as well as state of origin. Florida has been a refuge for north erners wishing to escape cold climates for decades, so there is a probability some, if not many, Florida high school band directors were not born and raised in Florida.
112 Table 22 Summary of Predictors included in Regr ession Models and Discriminant Function ________________________________________________________________________ Significant Predictors Concert Marching St.C oncert. Att. Cmp. Ma rch. Att. Balance ______________________________________________________________________________________ Teaching Styles Time Efficiency + + + + Music Concept Lrn + + + Nonverbal Motivation Assertive Teaching Group Dynamic Positive Learning Env. Personality Facets Immoderation + + + Assertiveness + + Modesty Imagination Cheerfulness Anxiety Dutifulness Emotion + Adventurousness ______________________________________________________________________________________ It is important to point out that while ba nd ratings were used as criterion variables throughout this study, they should not be consid ered an ultimate criterion of success for a band director, or a band program A principal reason for their use in this study is that these ratings are published on publicly availa ble websites dating back several years, which makes them a convenient source of data. Most schools have ratings available over several consecutive years, a nd the judging criteria for bot h the Florida Bandmasters Association and the Florida Marching Band Co alition are both detailed and consistent which helps establish the validity of their use as a measure of achievement. With high reliabilities indicated in chap ter 4 it can now be stated that these band ratings are also a reliable measure of band performance. This finding is in agreement with the literature,
113 which found music festival contest ratings ar e reliable measures over time (Burnsed, Hinkle, & King, 1985; Guegold, 1989; Oakley, 1975) Still, a director whose sole goal is to seek high band ratings may neglect other, ve ry important goals of a band program such as examining a breadth of literature, including literature which is at a level of difficulty for which the band may not be able to earn th e highest ratings if it were performed at a festival. The teaching style Time Efficiency seems to be particularly noteworthy due to its significant correlations with all of the criter ion variables. These correlations are also among the strongest correlations in this research. The nature of Time Efficiency is for a teacher to strive to accomplish as much as po ssible during time spent with students. This teaching style is particularly well suited to wards large ensemble settings where a teacher who uses time efficiently can rehearse ma ny parts of the music, answer many student questions, and address many musical concep ts. Gumm (2003a) wrote, Â“Time Efficiency is worth considering in a performance or active learning situation. The skills of Time Efficiency are especially important to overcome bad habits of over-dwelling, fragmenting, and flip-floppingÂ” (p. 41). Based on the results of the data analysis, Time Efficiency is an important part of being a successful high school band director. Wasting rehearsal time might mean students get less pl aying time, receive less feedback from the director or instructors, get less experience developing physical playing or marching skills, learn less literature, learn fewer concepts, a nd have less time to reflect on performances to consider how to make improvements for the future. Music Concept Learning is another pr edictor variable, which has a strong correlation with concert and marching band ra tings and state FBA concert band festival.
114 This requires good questioning skills and the ab ility to generate critical thinking skills. Music Concept Learning entails concepts of music theory and history, understanding the expressive properties of music, understand ing musical terminology, getting students to think critically in drawing comparisons betw een musical examples including evaluations of quality, and getting students to devel op problem solving techniques to address performance issues such as interpretation (Gumm, 2003a). Teachers should strive to refine these delivery and questioning techni ques to help develop studentsÂ’ factual knowledge about the music they are play ing as well as music in general. Two other teaching styles which significantl y correlated with concert band ratings are Artistic Music Performance and Student Independence. Artistic Music Performance is made up of skills such as aural imagery of sound, psychomotor skills such as breathing correctly and physically playing instruments, and teacher modeling of sound verbally or with an instrument (Gumm, 2003a). These are particularly important skills in developing studentsÂ’ ability to focus on good sound and perform accurately with a mature and musical sound. These are the only things concer t bands are evaluated on at festival, while marching bands also have movement and physic al coordination elements to consider. This may be one of the reasons the corre lation was stronger for concert band than marching band. Student Independence is an impo rtant teaching style where the teacher is more of a coach or guide than a director. To foster Student Indepe ndence a teacher must involve students in dialogue and discussi on, find out what is im portant to students, encourage students to be creative and imagin ative, involve the students in leading or governing their peers, their section, or the ensemble. St udent Independence may be a
115 significant factor in jazz improvisation, developing strong student leaders, and being successful at solo and ensemble events. Based on the results, it is possible to dis cern personality facets and teaching styles which contribute to a high school band di rectorÂ’s success with a concert band. The director must use every mo ment of rehearsal for meaningful teaching and learning experiences and be confident that he or she is capable of accomplis hing the tasks at hand. The director must be able to teach musi cal concepts effectively through questioning skills, encouraging critical thinking, and developing an understanding of music in the students. The director must be assertive and ab le to take charge. A director who is timid or reluctant to take charge of the class ma y have difficulty managi ng student behavior, or may simply not do what needs to be done. Asse rtiveness is a measur e of leadership and initiative, one who can take ch arge and manage classroom act ivities for the students. The passion and emotional investment a successful concert band director permits himself or herself to indulge in to be expressive may carry over to other aspects of life where overindulgence may manifest itself. The results indicate a successful marching band director might be one who takes advantage of every moment of rehearsal to accomplish important teaching and learning activities. Time management can be very impor tant when there are potentially very large numbers of students who need to learn how to perform music, often from memory, while moving in intricate patterns across a field. As in concert band, directors need to help students understand musical concepts and be able to develop critical thinking skills. Success in marching band may also be tied to a degree of being down to earth and less mired in fantasy (Imagination facet). Dea ling with the here-and-now in a practical,
116 sensible fashion is indicated as contributi ng to higher marching band scores. Amidst the pomp and pageantry, bold sounds and vivid vi suals of a marching band show, a degree of pride from the director may naturally be tied to success more than a humble or selfeffacing director. Pride is ofte n a hallmark of a marching band programs and is even the bandÂ’s verbal response to a call to attenti on for some programs. Despite this pride, marching band directors may not be the most predisposed towards positive emotions such as jollity, lightheartedness, and joy. Many band directors take th eir responsibilities to the marching band very seriously and perhaps assu me the same serious manner in everyday life. Finally, the successful marching band di rector may be inclined to be cool-headed and calm. Worry and anxiety may be associated with weakness, while the director who is already bold and proud takes challenges as they come with a cool head and responds to problems and dilemmas with the level-he aded sensibility a lluded to above. More frequent participation in state FBA concert band festival must be linked to better ratings at concert band, as it is not possible to partic ipate in the state festival without first earning a supe rior at district in given year. Therefore, the two are integrally linked. As above, the director must be able to use every moment of class time for teaching and learning activities, and must be able to communicate conceptual and musical knowledge effectively through disc ussion and questioning. Teachers who more frequently attend state FBA concert band fe stival may spend less time on classroom discipline, possibly because he or she estab lished standards for behavior from an early point and students meet those expectations thereby removing the need for constant policing. As with concert band ratings, the pass ion of the music may be tied to personal habits of indulgence. Related to this, thes e directors may be more concerned with the
117 music than studentsÂ’ feelings. Teachers focuse d on the highest levels of refinement and nuance may be less willing to give up their control of the ensemble for student leaders and may be more inclined to direct the gr oup themselves; high school students may not be aware of how best to solve musical proble ms at this particularly intense level of musical detail a nd perfection. Personality and teaching style were only ab le to predict 11% of the variation in FMBC competitive marching band event partic ipation. Therefore these factors, while significant, make up only a small part of the va riation in frequency of attendance. It is also important at this point to note it may not be desirable fo r every director to increase their attendance at competitive marching band events. An over-emphasis on competition can be counterproductive. The first component in predicting frequency of attendance at FMBC competitive marching events is Time Efficiency. As indicated with marching band, a heavy schedule of competitive marching band performances requires using every moment of every rehearsal to its fullest, developing marching and musical fundamentals, working on the show, and so forth. Those who attend more marching competitions may be more likely to maintain focus on the same activities during rehearsal for a significant length of time with lit tle variation, maintain a stable appearance and location throughout rehearsal, and prefer to use language to communicate rather th an eye contact or gestures. Those who attend fewer marching competitions are more likely to vary the pace of rehearsals, change the kinds of activities th at take place during rehearsal time, move around the room, make more use of eye cont act and gesture (conducting and otherwise). Similar to marching band, the band director who frequently showcases his or her ensemble in numerous venues is less likely to be self-effacing or ev en humble. He or she
118 may feel the hard work students have put fort h is of great quality and therefore needs to be shown as much as possible. Lastly, those who attend marching competitions more often may have less of a sense of respons ibility than those who moderate their competition schedule to one or two events per year. As stated earlier, excessive focus on competition may be a result of a director overtaxing the students. Directors attending fewer competitions tended to have a stronger sense of responsibility. The data help establish an impression of personality and teaching style differences between the balanced director and the marchi ng-oriented director. Ba lanced directors are more likely to take charge and be an asser tive leader, although they are more comfortable with routine and less eager to experience ne w things. These directors may also permit themselves to be swept away by the passi on and emotional elements of music making, which may represent itself in other aspects of life outside th e classroom such as indulging in personal pleasures. It is noteworthy that there are no concert-or iented directors; th is itself suggests some important possibilities. It may be th at marching band is enjoyable and exciting enough for band directors so even those who prefer concert band still put forth equal effort in that domain. It may also be th at band directors donÂ’t see concert band as something to focus on to the exclusion of ot her professional responsibilities. However, the data suggest a more likely situation is that those who succeed at concert band activities and focus on skills and knowledge pe rtinent to the concert band also succeed with their marching bands. The data reveal marching-oriented directors have the same mean score at marching as balanced direct ors, and the small amount by which marchingoriented directors surpass bala nced directors at marching comp etitions is not significant.
119 To be classified as marching-oriented a director must score .5 points higher with marching band than concert band, attend at least one marching competition annually, and not participate in state concert band festival. This definition was meant to outline what might be considered a Â“marching band specia list.Â” The problem is the Â“marching band specialistÂ” is not a marching band specialist at all, but simply a director who attends significantly more marching competitions and is significantly less successful at concert band. While the regression models which explain the variance in ratings for the criterion variables are all significant, none of them expl ains a great deal of variance. Combinations of teaching styles and personality facets expl ain just over 20% of the variance in concert band ratings, marching band rati ngs, and attendance at state concert band festival, and only 11% of the variance in attendance at marching band competitions. This indicates there is a great deal more which influences band ratings than band director teaching style and personality. The literature indicates aspe cts of the school, stude nts, administration, band instruments, literature being performed, and numerous other variables influence band ratings as well. However, as many of th ese are outside the immediate control of the band director, it is important to understand the potential influence of these aspects of the educational situation which the director can directly influence (teaching style and personality). Implications One of the most important implications of this research is personality and teaching style are significantly related to band ra tings, and consequently it is of value to be aware of oneÂ’s own personality type and teaching styles. Teacher educators may help
120 future educators by spending time administeri ng these or similar inventories so that educators are aware of their current tendencies. From this point, discussions and selfreflection on how these affect teach ing may lead to improved teaching. Specific implications for band director s include the need to focus on those teaching styles which indicate significant correlations with success. Large ensemble rehearsals need to be run smoot hly and efficiently, and it is in the intere st of directors and students to make the most of this time. Li kewise, developing skills to teach music and music concepts and focusing on performing musi cally and artistically with good tone and a mental image of what the sound should be ma y be important factors of success as well. Another important personality facet is Se lf-Efficacy. This implies a band director ought to develop a value for a sense of confid ence in his or her competence as a music educator. If a director does not feel confident in his or her competence but still values it, this may drive that director to seek out ways to improve his or her approach to teaching. An important note is while several teach ing styles are highly correlated with success in marching or concert band, relatively few of the personality facets are. This may be good news, as it seems likely that it would be easier for a person to alter or improve the way they teach with an understand ing of what is effective when compared to personality. Personality, while not immutable, is an aspect of a person which is perhaps less likely to fluctuate much over time, espe cially when a person has reached adulthood (McCrae & Costa, 2003). If a pers on finds that he or she has low levels of a personality facet that seems to be an important part of success in being a ba nd director, it is not necessary to despair and give up the profession, but at leas t be aware that this is a
121 personality aspect which may need to be alte red, or at least controlled for while in a professional setting. Perhaps one of the most important implic ations for high schoo l band directors is the need to focus on the concert band as th e center of the band program, based on the findings that balanced directors are more su ccessful at concert band festivals and equally successful at marching events compared to ma rching-oriented direct ors. In the Florida Bandmasters Association, marchi ng band ratings are weighted to favor musicianship over all other aspects. Even if a band earns rati ngs one division lower in marching and general effect than they do in both music captions, the rating will go in favor of what was earned in the music captions. The data here indi cate those who balance concert band and marching band do just as well in marching band (competitive and otherwise) as marching-oriented subjects, but are much mo re successful in concert band. This reflects RickelsÂ’ (2008) finding that marching bands scored higher when they began working on concert band music earlier in the school y ear. This might imply that a high school band director should concentrate on the field s how during summer band camp, but when the school year begins band cla ss should focus on concert music and developing music fundamentals while the marching activities are relegated to af ter-school rehearsals. This would also ensure that students are learning a wider variety of literature during the year rather than spending the months of A ugust through mid-November only studying a seven-minute marching band show and perhaps a handful of stand tunes. Playing a wider variety of literature may also give students more opportunities to develop music-reading skills and be able to interpret and be expr essive in a wider variety of literature.
122 Recommendations for Further Research There are a number of dire ctions research could take from this study. Some of these directions include repl ication of the study under diffe rent circumstances. This study could be reproduced in other states or c ountries where similar band programs exist. Results from different geographical locations and different cultura l climates may offer worthwhile insights. It may also be useful to replicate this study with other educational levels and other areas within the music education profession. The literature review indicat ed there are many differences in personality between elementary and secondary music education majo rs, and this may yield important findings both in determining a prototypical model of an elementary general music specialistÂ’s personality or teaching style (or middle schoo l choir director or high school orchestra teacher, etc.) but also in determining which of these elements correlate significantly with various measures of success in these fields. Another important direction might be to examine high school band directorsÂ’ teaching styles and personalities when compared with different measures of success, such as student recruitment and retention, stude nt reports of satisf action with the band program, percentage of students who continue to be active in music after graduating from high school, and other measures as may be deemed worthy of investigation. A longitudinal study which examines how successfully teaching style and personality predictors predict success in ma rching and concert band might reveal useful information. If music education majors took the MTSI and IPIP-NEO during their student teaching experiences, results could be examin ed and the ratings these teachers achieved
123 over the next several years could be examined to determine how accurate the predictions were. It is clear some of the predictor vari ables show significant relationships with criterion variables, but the other predictors should not therefore be considered as being without value. Many predictors might have a strong relationship with different aspects of band directors or music educators in general, such as elementary music teachersÂ’ success at getting students to improvi se a rhythm over a rhythmic ostinato, or the ability of orchestra directors to recruit students from a f eeder program. It may be very beneficial to explore which teaching styles or personality facets correlate str ongest with different measures of professional success in different professional roles within music education. It may be beneficial to examine persona lity traits and teaching styles of high school band directors in relation to why co llege freshmen choose to continue or discontinue musical studies. There may be a re lationship which is more likely to generate a degree of Â“burnoutÂ” in graduating seniors. As suggested by the findings to research question 4, there may be director-related factors other than personality and teaching st yle which influence frequency of attendance at marching competitions, and possibly other f actors such as band ratings as well. These Â“other factorsÂ” may be related to the di rectorÂ’s background, prof essional experiences, training, philosophy, or even a more global conception or Gestalt of the director. The exploratory construct included in this study, balance, seems to have effectively identified band directors who ba lanced effort and success with both the concert and marching band res ponsibilities of their jobs, a nd differentiated them from those who are marching-oriented. It may be beneficial to furt her explore the implications
124 of this variable in other geographical locations It may be interesting to determine typical characteristics of balanced and marching-oriented subjects in ways outside of personality and teaching style, such as student opinions of satisfaction, propor tions of students who continue with instrumental music after gra duation, rate of profe ssional burnout, and other factors which may shed furt her light on this phenomenon.
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139 Appendix A Descriptive Statistics for Criterion Variables by Gender ___________________________________________________________ Criterion Variable gender n M SD skew. kurt. ___________________________________________________________ Marching male 139 1.40 .47 1.38 1.67 female 24 1.76 .64 .69 -.26 Concert male 139 1.70 .53 .73 -.24 female 26 2.07 .77 1.46 1.90 FMBC attend male 148 1.43 1.34 .63 -.82 female 27 .87 1.02 .95 .02 FMBC score male 109 72.80 9.51 -.18 -.94 female 15 67.00 7.74 .24 -.94 State conc. attend male 127 .36 .40 .56 -1.32 female 22 .18 .34 1.69 1.56 State conc. score male 64 1.73 .61 1.15 2.01 female 6 1.78 .34 .64 .57 ___________________________________________________________
140 Appendix B Descriptive Statistics for Criterion Variables by Academic Degree ___________________________________________________________ Criterion Variable degree n M SD skew. kurt. ___________________________________________________________ Marching Bachelors 90 1.53 .55 1.19 .86 Masters 67 1.37 .46 1.31 1.48 Specialist 4 1.10 .16 1.66 2.62 Concert Bachelors 89 1.83 .57 .99 .92 Masters 70 1.68 .61 1.43 3.33 Specialist 4 1.33 .12 -1.30 .98 FMBC attend Bachelors 95 1.35 1.35 .82 -.52 Masters 73 1.30 1.26 .64 -.72 Specialist 4 2.75 .74 1.72 3.27 FMBC score Bachelors 69 71.30 9.90 .09 -.99 Masters 50 72.83 9.12 -.30 -.93 Specialist 4 76.88 7.09 -.02 -4.65 State conc. attend Bachelors 81 .28 .37 .90 -.71 Masters 62 .40 .44 .41 -1.62 Specialist 4 .33 .27 .06 1.50 State conc. score Bachelors 34 1.82 .65 1.37 2.80 Masters 32 1.63 .55 .68 -.32 Specialist 3 1.67 .00 -1.73 ___________________________________________________________ *unable to calculate
141 Appendix C Descriptive Statistics for Criterion Variables by Instrument ___________________________________________________________ Criterion Variable Instrument n M SD skew. kurt. ___________________________________________________________ Marching Flute 2 1.75 .12 * Bassoon 5 1.40 .65 1.71 2.67 Clarinet 15 1.43 .50 1.04 -.15 Saxophone 21 1.44 .46 1.23 1.82 Trumpet 49 1.38 .53 1.75 2.67 Horn 10 1.63 .69 1.05 .02 Trombone 20 1.54 .56 .95 .68 Euphonium 11 1.62 .56 1.53 2.98 Tuba 8 1.48 .31 -.42 -.52 Percussion 16 1.34 .42 1.45 1.56 Piano/Keybd. 2 1.38 .53 * Concert Flute 3 2.64 1.41 1.62 Bassoon 5 1.41 .35 .29 -1.31 Clarinet 16 1.63 .60 1.42 2.08 Saxophone 22 1.64 .50 .81 .03 Trumpet 48 1.69 .58 1.03 .55 Horn 10 1.89 .67 .46 -.38 Trombone 19 1.88 .44 .73 -.24 Euphonium 11 1.82 .75 1.87 4.23 Tuba 9 1.93 .56 -.12 -.39 Percussion 16 1.76 .53 .48 -1.34 Piano/Keybd. 2 1.52 .32 * FMBC attend Flute 3 .44 .77 1.73 Bassoon 5 1.27 .72 -.07 -1.82 Clarinet 15 .97 1.20 1.19 -.02 Saxophone 23 1.46 1.43 .42 -1.47 Trumpet 51 1.37 1.27 .60 -.82 Horn 11 1.09 1.16 .42 -1.36 Trombone 20 1.27 1.06 .58 -.77 Euphonium 11 1.68 1.74 .51 -1.23 Tuba 9 .93 .13 2.56 7.08 Percussion 18 2.02 1.40 .06 -1.39 Piano/Keybd. 3 .22 .38 1.73 ____________________________________________________________
142 Appendix C: (Continued) Descriptive Statistics for Criterion Variables by Instrument (continued) ___________________________________________________________ Criterion Variable Instrument n M SD skew. kurt. ___________________________________________________________ FMBC score Flute 1 * * Bassoon 5 70.10 5.75 -.12 -2.79 Clarinet 10 66.80 10.63 .36 -.87 Saxophone 16 75.13 9.72 -.38 -1.32 Trumpet 36 73.39 9.06 -.20 -.74 Horn 6 75.36 4.36 .13 -1.05 Trombone 16 68.50 11.60 .39 -.88 Euphonium 7 74.61 9.48 -.62 -1.43 Tuba 7 67.99 7.62 1.50 2.90 Percussion 16 71.84 9.16 .17 -1.27 State Concert attend Flute 2 .17 .23 * Bassoon 3 .78 .39 -1.73 Clarinet 14 .52 .43 -.06 1.15 Saxophone 20 .32 .36 .62 -1.04 Trumpet 44 .36 .41 .59 -1.33 Horn 8 .19 .27 1.04 -.64 Trombone 18 .24 .39 1.34 .16 Euphonium 10 .13 .32 2.67 7.24 Tuba 8 .29 .42 .89 -1.16 Percussion 16 .40 .44 .49 -1.78 Piano/Keybd. 2 .34 .47 * State Concert score Flute 1 * * Bassoon 3 1.26 .13 -1.73 Clarinet 10 1.61 .58 1.63 3.20 Saxophone 10 1.51 .47 .32 -1.05 Trumpet 22 1.83 .73 1.54 2.73 Horn 3 1.83 .76 -.94 Trombone 6 1.71 .56 1.06 .99 Euphonium 2 1.67 .47 * Tuba 3 2.30 .18 1.56 Percussion 8 1.63 .39 -.51 -.80 ___________________________________________________________ *unable to calculate
143 Appendix D Descriptive Statistics for Predictor Variables by Gender __________________________________________________________________ Predictor variable gender n M SD skew. kurt. __________________________________________________________________ Assertive Teaching male 148 3.97 .54 -.08 -.48 female 28 4.11 .44 -.03 -1.02 Nonverbal Motivation male 148 3.88 .48 .07 .01 female 28 3.96 .43 -.53 .29 Time Efficiency male 148 4.23 .46 -.31 -.60 female 28 4.15 .45 -.46 -.70 Positive Learning Environ. male 148 4.20 .49 -.41 .25 female 28 4.32 .42 -.22 -.31 Group Dynamics male 148 3.27 .55 .21 .34 female 28 3.30 .56 -.73 -.25 Music Concept Learning male 148 3.76 .52 -.48 1.20 female 28 3.68 .49 -.41 .11 Artistic Music Performance male 148 3.53 .56 -.13 .25 female 28 3.47 .56 -.40 .97 Student Independence male 148 3.44 .63 .02 -.13 female 28 3.40 .52 1.01 1.56 Neuroticism male 131 2.59 .59 .60 1.06 female 26 2.70 .69 -.31 -.81 Extraversion male 131 3.60 .49 -.37 .36 female 26 3.57 .66 -.61 -.60 Openness to Experience male 131 3.46 .48 .08 .35 female 26 3.52 .43 .29 .85 Agreeableness male 131 3.81 .46 -.32 -.04 female 26 3.98 .36 .01 -1.02 Conscientiousness male 131 4.05 .45 -.22 -.50 female 26 4.21 .43 -.40 -.33 __________________________________________________________________
144 Appendix E Descriptive Statistics for Predic tor Variables by Academic Degree __________________________________________________________________ Predictor variable Degree n M SD skew. kurt. __________________________________________________________________ Assertive Teaching Bachelors 96 4.00 .54 -.23 -.18 Masters 73 3.98 .51 .13 -.85 Specialist 4 4.05 .61 -1.94 3.82 Nonverbal Motivation Bachelors 96 3.89 .45 .25 .15 Masters 73 3.89 .50 -.22 .07 Specialist 4 4.18 .39 -.32 -3.03 Time Efficiency Bachelors 96 4.16 .50 -.26 -.88 Masters 73 4.28 .38 -.13 -.28 Specialist 4 4.79 .25 -1.54 2.89 Positive Learning Environ. Bachelors 96 4.23 .48 -.58 .14 Masters 73 4.19 .48 -.21 -.61 Specialist 4 4.29 .42 .94 1.50 Group Dynamics Bachelors 96 3.23 .56 .05 .12 Masters 73 3.30 .51 -.02 .04 Specialist 4 3.71 .26 .00 -3.30 Music Concept Learning Bachelors 96 3.71 .61 -.51 .57 Masters 73 3.78 .51 -.54 1.70 Specialist 4 3.89 .41 -1.85 3.41 Artistic Music Performance Bachelors 96 3.46 .52 -.17 -.12 Masters 73 3.61 .54 .07 -.67 Specialist 4 3.32 1.26 -1.24 1.25 Student Independence Bachelors 96 3.42 .61 .28 -.10 Masters 73 3.43 .62 .03 .40 Specialist 4 3.36 1.05 -.24 -3.15 Neuroticism Bachelors 86 2.60 .55 .03 -.58 Masters 67 2.65 .66 .69 1.10 Specialist 4 2.22 .74 1.19 2.30 Extraversion Bachelors 86 3.56 .52 -.69 .29 Masters 67 3.63 .53 -.14 -.09 Specialist 4 3.90 .35 -1.09 2.04 Openness to Experience Bachelors 86 3.43 .46 -.22 .03 Masters 67 3.49 .46 .44 .96 Specialist 4 4.18 .34 1.45 2.51 Agreeableness Bachelors 86 3.87 .43 -.75 .55 Masters 67 3.79 .46 .08 -.05 Specialist 4 3.98 .83 -.97 -.26 Conscientiousness Bachelors 86 4.10 .43 -.11 -.68 Masters 67 4.04 .47 -.33 -.30 Specialist 4 4.30 .54 -1.85 3.51 __________________________________________________________________
145 Appendix F Descriptive Statistics for Predictor Variables by Instrument __________________________________________________________________ Predictor variable Instrument n M SD skew. kurt. __________________________________________________________________ Assertive Teaching Flute 4 3.82 .51 1.70 3.01 Bassoon 5 3.83 .53 .21 .49 Clarinet 16 3.91 .44 .10 -1.05 Saxophone 23 4.18 .43 .67 -.83 Trumpet 51 3.91 .59 -.20 -.30 Horn 11 3.74 .44 .19 -1.68 Trombone 20 4.11 .51 -.20 -.42 Euphonium 11 3.88 .48 -.02 -.71 Tuba 9 3.90 .38 -.26 -1.20 Percussion 18 4.09 .56 -.09 -.49 Piano/Keybd. 3 4.14 .99 -1.57 Nonverbal Motivation Flute 4 3.81 .72 -.95 -.54 Bassoon 5 3.80 .42 -.31 -2.27 Clarinet 16 3.87 .56 -1.18 1.55 Saxophone 23 3.96 .55 -.13 .11 Trumpet 51 3.89 .39 .24 -.19 Horn 11 4.04 .55 .20 -1.64 Trombone 20 3.90 .48 .33 -.36 Euphonium 11 3.67 .24 -.65 -.66 Tuba 9 3.92 .45 .25 -.24 Percussion 18 3.89 .54 .38 .32 Piano/Keybd. 3 3.95 .58 .72 Time Efficiency Flute 4 3.93 .59 .71 1.79 Bassoon 5 4.20 .37 .54 -1.49 Clarinet 16 4.18 .39 -.59 -.38 Saxophone 23 4.22 .41 -.05 .21 Trumpet 51 4.22 .51 -.38 -.82 Horn 11 4.19 .58 -.26 -1.50 Trombone 20 4.35 .41 -.78 .95 Euphonium 11 3.94 .35 -.53 -.43 Tuba 9 3.97 .42 -.65 -1.68 Percussion 18 4.44 .34 .08 -.91 Piano/Keybd. 3 4.62 .54 -1.60 Positive Learning Environ. Flute 4 4.29 .42 .94 1.50 Bassoon 5 4.17 .49 1.65 3.33 Clarinet 16 4.35 .56 -1.14 .34 Saxophone 23 4.23 .46 .27 -1.12 Trumpet 51 4.20 .55 -.44 -.78 Horn 11 4.18 .46 -.86 -.23 Trombone 20 4.29 .41 -.58 .55 Euphonium 11 4.12 .35 -.71 -.41 Tuba 9 3.97 .61 -.88 1.78 Percussion 18 4.25 .37 .51 -.55 Piano/Keybd. 3 4.10 .46 -1.55 __________________________________________________________________
146 Appendix F: (Continued) Descriptive Statistics for Predictor Variables by Instrument (continued) __________________________________________________________________ Predictor variable Instrument n M SD skew. kurt. __________________________________________________________________ Group Dynamics Flute 4 2.89 .62 .83 -.04 Bassoon 5 2.89 .71 .29 -.41 Clarinet 16 3.34 .54 .24 1.00 Saxophone 23 3.34 .48 .25 .49 Trumpet 51 3.29 .59 -.10 -.07 Horn 11 3.08 .49 .29 -.22 Trombone 20 3.25 .63 .25 .69 Euphonium 11 3.21 .45 .05 -.64 Tuba 9 3.30 .51 -.63 -1.45 Percussion 18 3.37 .40 .25 .88 Piano/Keybd. 3 3.05 .68 -1.39 Music Concept Learning Flute 4 3.50 .55 1.38 2.36 Bassoon 5 3.51 .41 1.08 -.06 Clarinet 16 3.80 .50 -.16 -1.24 Saxophone 23 3.89 .39 .00 -.31 Trumpet 51 3.85 .51 -.44 .43 Horn 11 3.55 .45 .33 .15 Trombone 20 3.66 .61 -.93 1.80 Euphonium 11 3.64 .40 .08 -1.19 Tuba 9 3.71 .61 -.34 -.69 Percussion 18 3.60 .32 .36 .06 Piano/Keybd. 3 3.37 .99 -1.64 Artistic Music Performance Flute 4 2.93 .64 -1.57 2.42 Bassoon 5 3.11 .80 1.50 2.04 Clarinet 16 3.66 .41 -.57 .32 Saxophone 23 3.67 .71 -.91 2.24 Trumpet 51 3.56 .52 .07 -.83 Horn 11 3.36 .58 .43 -1.24 Trombone 20 3.58 .51 -.30 -.62 Euphonium 11 3.49 .31 -.51 .72 Tuba 9 3.59 .44 .45 1.17 Percussion 18 3.42 .55 .10 -.10 Piano/Keybd. 3 3.14 .62 1.63 Student Independence Flute 4 3.21 .50 .00 -5.21 Bassoon 5 3.03 .74 1.73 3.25 Clarinet 16 3.48 .61 -.10 -.62 Saxophone 23 3.65 .69 .17 .22 Trumpet 51 3.52 .62 .19 -.46 Horn 11 3.08 .57 .64 -.75 Trombone 20 3.34 .63 .21 .95 Euphonium 11 3.42 .36 .36 -.09 Tuba 9 3.35 .54 .70 1.16 Percussion 18 3.41 .53 .43 -.95 Piano/Keybd. 3 2.81 .99 -.72 ________________________________________________________________________
147 Appendix F: (Continued) Descriptive Statistics for Predictor Variables by Instrument (continued) ______________________________________________________________________________ Predictor variable Instrument n M SD skew. kurt. __________________________________________________________________ Neuroticism Flute 3 2.68 .71 -.68 Bassoon 5 2.87 .71 .34 1.83 Clarinet 15 2.52 .46 -.04 -.14 Saxophone 21 2.58 .52 -.24 -1.15 Trumpet 47 2.65 .68 .96 1.68 Horn 10 2.58 .66 .07 -.35 Trombone 17 2.57 .54 -.20 -1.29 Euphonium 10 2.62 .66 .05 -.39 Tuba 8 2.53 .63 .08 -2.37 Percussion 16 2.75 .60 -.03 -.25 Piano/Keybd. 3 1.99 .74 1.58 Extraversion Flute 3 3.54 .61 -1.64 Bassoon 5 3.13 .68 -1.19 2.37 Clarinet 15 3.48 .53 -.51 -.81 Saxophone 21 3.72 .48 -.52 -.60 Trumpet 47 3.63 .48 .17 .13 Horn 10 3.65 .57 -.34 -.148 Trombone 17 3.49 .57 -.02 -.90 Euphonium 10 3.28 .57 -1.17 2.04 Tuba 8 3.67 .51 -.66 -.03 Percussion 16 3.71 .45 -1.78 6.07 Piano/Keybd. 3 3.92 .55 .67 Openness to Experience Flute 3 3.24 .12 1.73 Bassoon 5 3.43 .39 -.52 -2.25 Clarinet 15 3.31 .50 .81 1.40 Saxophone 21 3.43 .52 -.98 .45 Trumpet 47 3.58 .53 .30 .16 Horn 10 3.67 .39 -.20 -1.92 Trombone 17 3.34 .46 -.39 -.83 Euphonium 10 3.50 .25 .91 -.12 Tuba 8 3.33 .42 1.87 3.40 Percussion 16 3.46 .44 .03 1.25 Piano/Keybd. 3 3.54 .43 -1.73 Agreeableness Flute 3 3.74 .33 .37 Bassoon 5 3.85 .55 -1.70 3.00 Clarinet 15 3.93 .42 -.03 -1.58 Saxophone 21 3.69 .45 -.27 .12 Trumpet 47 3.96 .51 -.54 -.01 Horn 10 3.65 .20 -.43 -.70 Trombone 17 4.01 .33 -.13 -.98 Euphonium 10 3.72 .29 .42 -1.12 Tuba 8 3.75 .61 -.96 1.52 Percussion 16 3.65 .45 -.55 -.73 Piano/Keybd. 3 4.10 .45 -1.72 ________________________________________________________________________
148 Appendix F: (Continued) Descriptive Statistics for Predictor Variables by Instrument (continued) _________________________________________________________________ Predictor variable Instrument n M SD skew. kurt. __________________________________________________________________ Conscientiousness Flute 3 4.56 .32 1.23 Bassoon 5 3.83 .31 -.60 -3.03 Clarinet 15 4.35 .41 -.68 -.94 Saxophone 21 4.08 .44 .16 -1.00 Trumpet 47 4.07 .49 -.47 -.42 Horn 10 3.92 .45 -.28 -.19 Trombone 17 3.96 .48 .06 -.89 Euphonium 10 4.02 .42 .20 2.30 Tuba 8 4.16 .24 -1.81 3.36 Percussion 16 4.00 .45 .16 .17 Piano/Keybd. 3 4.32 .20 .68 ______________________________________________________________________ *Unable to calculate
149 Appendix G BalanceFrequencies and Percentage by Gender _____________________________________________________________ Gender Balanced n % Marching n % _____________________________________________________________ Male 109 81.3% 25 18.7% Female 22 95.7% 1 4.3% Total 131 26 _____________________________________________________________
150 Appendix H BalanceFrequencies and Percentage by Academic Degree _____________________________________________________________ Degree Balanced n % Marching n % _____________________________________________________________ Bachelors 73 84.9% 13 15.1% Masters 52 80.0% 13 20.0% Specialist 4 100.0% 0 0.0% Total 129 26 _____________________________________________________________
151 Appendix I BalanceFrequencies and Percentage by Instrument _____________________________________________________________ Instrument Balanced n % Marching n % _____________________________________________________________ Flute 2 100.0% 0 0.0% Oboe 1 100.0% 0 0.0% Bassoon 4 80.0% 1 20.0% Clarinet 15 100.0% 0 0.0% Saxophone 18 85.7% 3 14.3% Trumpet 36 80.0% 9 20.0% Horn 8 88.9% 1 11.1% Trombone 17 89.5% 2 10.5% Euphonium 9 81.8% 2 19.2% Tuba 6 75.0% 2 25.0% Percussion 11 68.8% 5 31.2% Piano/Keybd. 2 100.0% 0 0.0% String 0 0.0% 1 100.0% Total 129 26 _____________________________________________________________
152 Appendix J Inter-item correlations for Teaching Styles ___________________________________________________________ MTSI dimension 1 2 3 4 5 6 ___________________________________________________________ Assertive Teaching Item 2 .35 Item 3 .34 .37 Item 4 .42 .32 .40 Item 5 .41 .33 .24 .29 Item 6 .28 .22 .40 .43 .15 Item 7 .27 .35 .15 .29 .25 .22 Nonverbal Motivation Item 2 .41 Item 3 .20 .27 Item 4 .36 .37 .10 Item 5 .10 .17 .23 .30 Item 6 .30 .30 .03 .34 .16 Item 7 .19 .29 .18 .29 .11 .31 Time Efficiency Item 2 .17 Item 3 .25 .23 Item 4 .29 .39 .38 Item 5 .16 .43 .25 .44 Item 6 .08 .34 .28 .40 .27 Item 7 .49 .37 .30 .38 .31 .23 Positive Learning Environment Item 2 .29 Item 3 .27 .32 Item 4 .24 .30 .36 Item 5 .40 .34 .33 .31 Item 6 .34 .42 .41 .48 .35 Item 7 .40 .30 .34 .43 .59 .40 Music Concept Learning Item 2 .35 Item 3 .28 .21 Item 4 .17 .36 .38 Item 5 .19 .28 .34 .50 Item 6 .27 .34 .15 .31 .38 Item 7 .32 .37 .35 .40 .49 .30 ___________________________________________________________
153 Appendix J: (Continued) Inter-item correlations for Teaching Styles (continued) ____________________________________________________________ MTSI dimension 1 2 3 4 5 6 ____________________________________________________________ Artistic Music Performance Item 2 .27 Item 3 .46 .52 Item 4 .39 .37 .49 Item 5 .24 .06 .08 .17 Item 6 .24 .33 .29 .18 .30 Item 7 .28 .33 .48 .43 .19 .27 Student Independence Item 2 .65 Item 3 .48 .54 Item 4 .45 .49 .47 Item 5 .20 .29 .31 .30 Item 6 .44 .38 .40 .52 .42 Item 7 .48 .56 .54 .50 .36 .59 ___________________________________________________________
154 Appendix K Inter-item correlations for Personality Facets ____________________________________________________________ Pairs of Items Facet 1 & 2 1 & 3 1 & 4 2 & 3 2 & 4 3 & 4 ____________________________________________________________ Neuroticism Anxiety .48 .26 .44 .40 .39 .43 Anger .66 .74 .43 .65 .51 .46 Depression .43 .74 .46 .66 .55 .57 Self Consciousness .39 .54 .30 .44 .18 .27 Immoderation .23 .29 .34 .21 .29 .35 Vulnerability .60 .30 .36 .41 .39 .35 Extraversion Friendliness .60 .40 .45 .54 .63 .39 Gregariousness .60 .44 .66 .36 .54 .63 Assertiveness .49 .62 .55 .48 .36 .50 Activity .57 .12 .00 .31 .18 .24 Excitement Seeking .42 .19 .28 .28 .36 .33 Cheerfulness .37 .34 .46 .36 .42 .57 Openness to Experience Imagination .38 .29 .19 .52 .48 .68 Artistic Interest .22 .30 .35 .19 .18 .41 Emotion .16 .25 .07 .12 .21 .17 Adventurousness .34 .36 .36 .51 .51 .46 Intellect .13 .29 .20 .34 .63 .49 Liberalism .40 .90 .34 .38 .20 .34 Agreeableness Trust .54 .67 .76 .60 .56 .65 Morality .35 .55 .26 .32 .19 .34 Altruism .58 .17 .46 .38 .41 .28 Cooperation .34 .31 .25 .56 .34 .42 Modesty .47 .45 .36 .81 .23 .26 Sympathy .51 .37 .38 .33 .39 .24 Conscientiousness Self Efficacy .38 .43 .39 .33 .40 .47 Orderliness .58 .67 .54 .62 .55 .57 Dutifulness .35 .15 .67 .35 .33 .10 Achievement Striving .55 .38 .49 .32 .45 .37 Self Discipline .48 .48 .32 .41 .23 .46 Cautiousness .62 .61 .66 .71 .77 .74 ____________________________________________________________
About the Author At the time of defense, Timothy J. Groulx is contracted to be Assistant Professor of Music Education at the University of Evansville in Indiana where he will teach instrumental and general music education cour ses and assist with th e universityÂ’s bands. Prior to this appointment, Mr. Groulx served as a graduate as sistant at the University of South Florida where he taught woodwind and br ass techniques courses, assisted teaching other music education courses, supervised student teachers, and assisted with the marching and concert bands. After completing B achelorÂ’s and MasterÂ’s degrees in music education at Oberlin Conserva tory in 1999, Mr. Groulx taught 5th-12th band programs for two years in central Ohio followed by five years of high school band in the Tampa Bay area, and beginning band programs in th e Tampa Bay area K-8 Catholic schools concurrent with his doctoral st udies. Mr. Groulx is a Nationa l Board Certified Teacher in Music.