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Running head: MUSIC PARTICIPATION & ENGAGEMENT & ACADEMICS. Success, and School Engagement in the Metropolitan Nashville Public Schools:

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Music Participation & Engagement & Academics 1 Running head: MUSIC PARTICIPATION & ENGAGEMENT & ACADEMICS Evaluation of the Impact of Music Program Participation on Students Musical and Academic Success,
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Music Participation & Engagement & Academics 1 Running head: MUSIC PARTICIPATION & ENGAGEMENT & ACADEMICS Evaluation of the Impact of Music Program Participation on Students Musical and Academic Success, and School Engagement in the Metropolitan Nashville Public Schools: A Comprehensive Test of Pathways and Contextual Factors Christopher M. Johnson Becky J. A. Eason The University of Kansas Word Count: 7,767 This research was funded by the MMU and MNPS. Music Participation & Engagement & Academics 2 Abstract The purpose of this project was to examine the effect of participating in music on student school engagement and academic achievement in a Metropolitan Nashville Public School district. Student records for the class of 2012 (N = 6,006) in a major urban school district were collected and examined for student personal characteristics, music participation, their indicated level of school engagement, and their academic achievements. These variables were examined using Structural Equation Modeling techniques. Results indicated that the quantity of Music Participation had an important effect on both the level of School Engagement and Academic Achievement. Conclusions indicate that more music involvement was advantageous to the school system s overall performance, and that steps being taken to engage a wider cross-section of students might well have a significant impact on the students academic lives. Music Participation & Engagement & Academics 3 Evaluation of the Impact of Music Program Participation on Students Musical and Academic Success, and School Engagement in the Metropolitan Nashville Public Schools: A Comprehensive Test of Pathways and Contextual Factors The extant literature is replete with investigations examining the effects of music study on the academic success of students. Researchers have paired music participation with various academic outcomes, including math and reading skills, as well as overall grade point averages. Most of these studies look at students in the elementary and middle grades. Several researchers have reasoned that, in the primary grades, student participation in music class is compulsory and therefore consistent across students in the same school. In high school, however, students have more degrees of freedom in selecting their classes, so any given student might take no music throughout high school, or might have many music credits. This variability makes the high school population more challenging to study. Therefore, though there are some investigations that look at secondary students and academic progress, those are far fewer. Most studies investigating connections between participation in music and general academic achievement have demonstrated that participation in music parallels increased academic achievement (Johnson & Memmott, 2006; Kinney, 2013; Perry, 1993). This relationship has been demonstrated with standardized tests in reading (Butzlaff, 2000; Neuharth, 2000), mathematics (Neuharth, 2000; Whitehead, 2001), grade point averages (Miranda, 2001; Zanutto, 1997), SAT scores (Butzlaff, 2000; Cobb, 1997; Miranda, 2001), and ACT scores (Cobb, 1997; Miranda, 2001). Some studies have shown that music participation did not affect academic achievement more than other variables investigated, but consequential academic gains were still noted (Andrews, 1997; Elpus, 2011; Perry, 1993). None of the studies found that participation in music negatively influenced academic progress. Music Participation & Engagement & Academics 4 Studies of elementary students have typically focused on those in third and/or fourth grade (when state assessments are regularly administered). Fitzpatrick (2006), Kinney and Forsythe (2005), and Wallick (1998) all looked at relationships between music participation and fourth grade assessment scores, and found that music participation, even when it required being pulled out of traditional instruction, was positively associated with test scores (or at least did not negatively affect them.) Gregory (1988) found that third-grade students receiving music instruction though the Leap Into Music curriculum made significant academic progress in mathematics. Similarly, Smithrim and Uptis (2005) found that participation in an arts-integrated curriculum led to modest but statistically significant gains in mathematics scores, but only after three years. Not every study showed consistent academic gains for young children who participate in music education. For example, a longitudinal study by Costa-Giomi (1999) showed that private piano lessons increased several measures of intelligence in the short term. However, those gains, as well as any academic gains, were not maintained through the entire three-year span of the study. By the end, both the experimental and control groups were relatively equivalent on both measures academic and intelligence scores. In another study, Kemmerer (2003) found that the number of hours spent in a general music class had no effect on reading skill scores. However, closer examination showed that the difference of time actually spent in music instruction between the groups was less than 18 minutes per week, so the case for differing amounts of instructional time did not appear to be strong enough to be significant. Further, the famous Mozart effect studies by Rauscher et al. (1993, 1995) were later found not to stand up to additional researcher scrutiny and replication (e.g., Schellenberg, 2005; Winner & Cooper, Music Participation & Engagement & Academics ). However, enough studies have found connections between music and academics that the topic merits further research. Rather than examining the effect of music on academics, some researchers have examined the converse relationship that of academics on music participation. Fitzpatrick (2006), Klinedinst (1991), and Miksza (2007) all found a predilection for high achieving students to choose to participate and to persist in music classes. Kinney (2008, 2010, 2013) determined that this relationship persisted into Middle School, but moreso for instrumental music participants than choral music participants, echoing the findings of Johnson and Memmott (2006) regarding statistically significant differences between instrumental and choral music participants. Scant research exists on the relationship between music participation and academics in the middle and high school years, but those studies that have been conducted reinforce the findings concerning elementary students. Research shows a relationship between statistically significantly higher academic achievement for students who participate in music education than for those who do not (Babo, 2004; Catterall, Chapleau & Iwanga, 1999; Cobb, 1997; Kinney, 2008; Miksza, 2007). Many of these researchers readily acknowledge that the evidence is unclear at best regarding which came first the academic achievement or the music participation but the relationship is undeniable. Perhaps the three most compelling reports on the relationship between music participation and academic achievement are by Cobb (1997), Catterall, Chapleau and Iwanaga (1999) and Butzlaff (2000). Cobb (1997) examined the ACT registration forms of 17,099 test takers and compared those who indicated that they had two or more classes or activities in music to those who had not. Findings indicated that individuals with a musical background had Music Participation & Engagement & Academics 6 significantly higher ACT scores on the English, reading, and science subtests. Scores for math were also higher for all subgroups, but not significantly so for African American students. Catterall, Chapleau and Iwanaga s 1999 investigation tracked approximately 25,000 students over the course of ten years. Results indicated that, regardless of socioeconomic background, secondary school students involved in music had significantly higher standardized test scores specifically mathematics proficiency than students not involved in music. This study examined several standardized tests, including the SAT. Similarly, Butzlaff (2000) completed a metaanalysis of all studies wherein a reading standardized test followed music instruction. He documented a consistent correlation between reading ability and music instruction. Though many claim that involvement in a variety of school activities aids academic progress, several studies have shown that not to be the case. In four investigations, music participation was the only activity shown to correlate significantly with academic progress (Miranda, 2001; Schneider, 2000; Trent, 1996; Underwood, 2000). Athletics and all other extracurricular activities did not show similar results. While clear trends arise in a study of music participation and academic achievement, the extant research on potential relationships between student engagement and activity participation (to include music participation) is far less focused. This lack of focus stems from the related difficulties of 1) defining engagement in a school setting, and 2) determining effective ways to measure engagement, once a definition has been selected. Qualitative studies (Bartolome, 2013; Smithrim & Uptis, 2005) tend to examine engagement via student self-reports and teacher observations regarding a sense of belonging, feelings of empowerment and commitment, and motivation for success. These studies have found that participation in music fosters a strong Music Participation & Engagement & Academics 7 sense of belonging and activity commitment (Bartolome, 2013), as well as a commitment to academic achievement (Smithrim & Uptis, 2005). Quantitative studies tend to define engagement in terms of future-predicting behaviors, such as motivational beliefs (Simpkins, Vest & Becnel, 2010) and aspirations (Darling, 2005), or the predictive power of present participation on future activity engagement (Mahoney, Cairns & Farmer, 2003). For these studies, participation was generally defined as level and intensity of activity participation (Brown & Evans, 2002; Darling, 2005; Mahoney, Cairns & Farmer, 2003). In general, all of these studies found positive effects resulting from activity participation, however positive effect was defined high aspirations for the future, greater engagement in activities over time, and evidence of interpersonal competence. However, the lack of a concise, agreed-upon definition for student engagement between the various studies makes it difficult to draw any definitive conclusions about relationships between music participation and student engagement. A further complication is that, in many of these studies, all arts offerings or extracurricular activities (to include music instruction offered during the school day) are lumped together into one activity variable (Brown & Evans, 2002; Darling, 2005; Mahoney, Cairns & Farmer, 2003; Smithrin & Uptis, 2005). While these studies undoubtedly have value of their own, they do not provide much clarity into the specific relationship between music participation and student engagement. In sum, the research indicates a somewhat reliable relationship, and some could even contend an association, between the study of music and academic performance on standardized reading and mathematics tests, on grade point averages, and on college entrance exams. Researchers have attempted to show how music may have had some causal effect on academic advancement; however, the furthest current research it can probably support is a concept of a Music Participation & Engagement & Academics 8 two-way interactionist position, such that music might catalyze or deepen learning in other academic areas, rather than to cause change. In the field of student engagement, the picture is less distinct. While there appears to be a relationship between activity participation and student engagement, more research is needed that separates the types of activities (sports, clubs, music, theatre) to tease out any differences in engagement that might exist between the various types of activity. The tools most researchers (who have examined data in this area) have most often used is ANOVA, often looking at differences between students who have studied music versus those who have not in a particular context categorical predictor variables. This is definitely a tried and true method, of which the results are usually very clear. It does, however, have the weakness of examining somewhat pervasive situations in an isolated manner (Mertler & Vannatta, 2010). In contrast, Structural Equation Modeling (SEM) is considered the second generation of multivariate statistical methods, and allows for continuous outcomes using continuous variables. Further, SEM allows those predictor variables to create continuous unobserved latent variables that can be compared (Lani, 2009). Though far from a perfect tool, SEM is an evolving instrument that can show substantially more than its predecessors. In the case of this project, we used SEM to test hypothetical latent constructs based on the input from several observed indicators. One key component of SEM is the construction of latent variables. Latent variables are hypothetical constructs (or factors), which are explanatory for some presumed reality that is not directly observable (Kline, 2011). An example of this type of variable could be the construct of musical talent. There is no single definitive measure of talent; however, researchers have used many different indicators (i.e. tests, audition results, and possibly other evaluations) that Music Participation & Engagement & Academics 9 together, might assess various facets of musical talent. The observed variables used as indirect measures of aspects of latent variables (or constructs) are referred to as indicators (Kline, 2011). In most cases of SEM, indicators are thought to be reflections of, or caused by, factors. However, in cases where indicators have temporal precedence over factors, or in cases where an indicator is thought to be covariate for a particular factor, the directional effects are reversed in the model. While at first, it might seem that SEM is dependent on many assumptions and allows the researcher to manipulate the numbers until they find the result they want, this is not actually the case. However, more classic analysis procedures of analysis of variance, multiple regression, t- Tests and the like, are also based on many assumptions regarding the properties of the data. SEM allows the researcher to specify, estimate, and evaluate the nature and veridicality of most assumptions inherent in his model. While not without assumptions, SEM actually allows the researcher to have many fewer assumptions than classic analyses, and then to test them (Little, 2013). The purpose of this project was to examine the effect of music participation on student school engagement and academic achievement in a Metropolitan Nashville Public School district. The value of this study is threefold. First, the analysis procedures of this study are different than any used prior study. Second, the data set used for this study was more comprehensive than any used in prior studies. Finally, this study has defined variables differently in many cases where variables have been defined using one measure in the past, this study has taken those single measures and combined them to create more comprehensive latent variables that are defined by the alliance of those multiple indicators. Music Participation & Engagement & Academics 10 Method Data Set The Metropolitan Nashville Public Schools (MNPS) is a large urban district in the center of the United States. The District has approximately 80,000 total students from more than 100 different countries, speaking more than 135 different native languages. There are more than 150 schools in the system, including more than 20 high schools. This district provided the researchers with de-identified student data for all students who were enrolled in MNPS in 9 th grade in The total N for the students was 6,006. In obtaining data for 9 th grade students 4 years ago, we were able to obtain graduation, delayed graduation, and drop out data. The student data provided were extensive, but the most cogent aspects of the data that were used from these central records are shown on Table 1. These observed categories of data were then placed into where the researchers hypothesized they most closely interacted to create a complete variable picture Latent Variable. Measures The first Latent Variable examined was that of Student Characteristics. Each student s sex was an observed variable that contributed to the student characteristics. Ethnicity was also a categorical variable that was theorized to influence student characteristics. SES as determined by free and reduced lunch was considered to be the 3rd variable that contributed to student characteristics. The elementary school environment, where that student went to school, and that school s characteristics, are theorized to be additional indicators for that latent variable. Finally, previous research has indicated that the type of student who takes up music when it becomes an elective is the one doing well in school. To control for the possible effect of this predilection, fourth-grade standardized test scores were included as covariates in this latent variable. Music Participation & Engagement & Academics 11 Table 1 Latent and Observed Variable List Student Characteristics Sex Ethnicity SES Elementary School characteristics the student attended 4 th grade basic skills Test Scores (pretest data) School or Site Characteristics Size SES (Free/Reduced Rate %) ESL Rate Music Participation Types (band, choir, orchestra, and each of the others) Total Semesters (number) Measures of School Engagement School Attendance Graduation Rates Disciplinary Reports Academic Gains Last Standardized Test Scores (State Assessments /ACT) GPA The second latent variable is that of School Characteristics for each high school student. The school characteristics examined included size of the school, percentage of ESL students, and the percentage of students on free and reduced lunch. These three indicators are theorized to be reflections of overall school characteristics. The third latent variable in the model is Music Participation. The indicators of music participation used in this study are how many semesters of the type of music in which the student was enrolled, and how many total semesters of music the student took. An attempt was made to determine a musical dose indicator, which assessed the quality of the musical education inherent Music Participation & Engagement & Academics 12 in each class and how many semesters of each class each student experienced, but this measure was determined to be too subjective for this stage of the research. The fourth latent variable is School Engagement. Many studies in the past have looked at school engagement, but most of them have done so by having students fill out a questionnaire. This study is determining the level of school engagement based on each student's attendance at school, the number and severity of discipline reports each student has in their record, and whether or not the student would graduate from high school on time, graduate late, transfer out of the system, or drop out. The final latent variable is that of Academic Achievement. This study examines three indicators of academic success. The first two are the English and Math scores from the standardized tests taken in the 12th grade, which in MNPS is the ACT. The third indicator of academic success is the student s high school grade point average. Resulting Model The theoretical construct that drives this study s model is based on research conducted by George Kuh and his associates on student engagement in higher education. Simply put, Kuh posits that students who are engaged and who make connections with their academic institution experience more academic success (Kuh, 200
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