Adolescence Using Three Measures of Music Participation
Order ID:89JHGSJE83839 Style:APA/MLA/Harvard/Chicago Pages:5-10 Instructions:
Adolescence Using Three Measures of Music Participation
The Impact of Music on Childhood and Adolescent Achievement
Darby E. Southgate, Ohio State University
Vincent J. Roscigno, Ohio State University
Objective. The study examines the association between music involvement and academic achievement in both childhood and adolescence using three measures of music participation: in school, outside of school, and parental involvement in the form of concert attendance. Methods. We review prior work pertaining to music’s impact on achievement and then draw from two nationally representative data sources (ECLS-K and NELS:88). Our analyses apply logistic and OLS regression techniques to assess patterns of music involvement and possible effects on math and reading performance for both elementary and high school students. Results. Music involvement varies quite systematically by class, and gender status, and such involvement holds implications for both math and reading achievement, and for young children and adolescents.
Notably, associations with achievement persist in our modeling even when prior achievement levels are accounted for. Although music does mediate some student background effects, this mediation is only minimal. Conclusions. Music participation, both inside and outside of school, is associated with measures of academic achievement among children and adoles- cents. Future work should further delineate the relevant processes of music in- volvement, as well as how background inequalities and music involvement intersect in relation to educational performance.
Music involvement has been publicly linked to student achievement—a presumed connection made all the more obvious in debates over cuts to high school elementary and high school music programs. Youth music partic- ipation is associated with higher matriculation rates (Aschaffenburg and Maas, 1997), higher rates of acceptance into medical schools (Thomas, 1994), lower rates of current and lifetime alcohol, tobacco, or drug abuse (Texas Commission on Drug and Alcohol Abuse, 1999), and lower rates of disruptive classroom behaviors (National Center for Educational Statistics, 1997). Despite these associations, there is much room for elaboration on the
nDirect correspondence to Darby Southgate, Department of Sociology, The Ohio State University, 238 Townshend Hall, 1885 Neil Ave. Mall, Columbus, OH 43210 hSouth- gate.5@sociology.osu.edui. Upon request, the corresponding author will share all data and coding information with those wishing to replicate the study. Thank you to Douglas Downey for his assistance in conceptualizing this work. We especially appreciate the helpful comments of the editor and the reviewers.
SOCIAL SCIENCE QUARTERLY, Volume 90, Number 1, March 2009 r 2009 by the Southwestern Social Science Association
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
i:/BWUS/SSQU/598/Southgate.5@sociology.osu.edu
music-achievement relation owing to the extant literature’s inability to define and empirically capture what music participation means. This is not to suggest, however, that the topic has not garnered the attention, both directly and indirectly, of educational theorists, psychologists, and sociol- ogists. It certainly has and for quite some time.
The connection between music and cognitive benefits (especially in math skills) is generally traced to the ancient Greek, Pythagoras, who in the fifth century BCE suggested that mathematical relationships were integral to physical properties, including music. Pythagoras envisioned a living cosmos comprised of ratios and he and his students devoted themselves to artic- ulating these relationships. Music and math were one and the same to the Pythagoreans. Pont (2004) argues that the correlation of math to the phys- ical, commonly credited to Pythagoras, existed prior to the Greeks. Indeed, recent excavations of clay tablets in and around Mesopotamia and Egypt, created sometime around 2000 BCE, show tunings (standardized mathe- matical ratios of stringed instruments).
Adolescence Using Three Measures of Music Participation
Such claimed associations between math, music, and cognition have per- sisted across time and cultures. Possible associations with children’s devel- opment made their way into the system of U.S. public education quite early on when Horace Mann, a founding thinker of public education, pushed for music inclusion in the core curriculum. The general consensus, which per- sists today, is that music is an important dimension of academic develop- ment. According to a Gallup Poll conducted and reported by the American Music Conference (2003): ‘‘Ninety-five percent of Americans believe that music is a key component in a child’s well-rounded education . . . more than three quarters of those surveyed feel schools should mandate music education.’’
Does music matter? In this article we build on prior theorizing and em- pirical work pertaining to music’s potential impact on student academic development and then analyze how various forms of music involvement shape reading and mathematics achievement. We begin with an overview of theorizing and empirical work pertaining to how and why music may be meaningful and then turn specifically to the question of academic achieve- ment.
Our analyses, which draw from both the National Educational Lon- gitudinal Survey (NELS:88) and the Early Childhood Longitudinal Survey (ECLS-K), allow us to address the achievement question directly and assess the reliability of patterns uncovered for small children as well as for ad- olescents. Given the breadth of research on stratifying processes as they are played out at educational (Alexander, Entwisle, and Thompson, 1987; Lucas, 1999, 2001; Roscigno and Ainsworth-Darnell, 1999) and familial levels (Lareau, 2002; Downey, 1995a, 1995b; DiMaggio and Ostrower, 1990), we also consider the degree of race, class, and gender disparities in music involvement. Significant group-level inequalities in music involve- ment would indeed be problematic to the extent that music holds impli- cations for achievement.
The Impact of Music on Childhood and Adolescent Achievement 5
Adolescence Using Three Measures of Music Participation
How and Why Music May Matter
Research from psychology as well as sociology has attempted to explain the importance of music for intellectual development by focusing on a variety of cognitive and social-developmental outcomes. Studies of the structured neuronal model of the cortex (Shaw and Brothers, 1989; Leng and Shaw, 1991) encouraged social scientists to discover that certain music positively affects the spatial-temporal scores of listeners during exams— something often referred to as the ‘‘Mozart effect’’ (Rauscher, Shaw, and Ky, 1993). Specifically, college students who listen to Mozart prior to taking a pencil-and-paper test of abstract spatial reasoning perform better than their counterparts who do not listen to Mozart. As an elaboration, others have suggested that variations in genre preference alter the effect (Steele, 2001). Although certainly intriguing, no study to date has provided definitive modeling that considers tonal complexity, musical genre preference, and sociocultural responses, though studies do point to arousal and mood as mediating the music effect on cognition (Thompson, Schellenberg, and Husain, 2001). Listening to music stimulates cognition (Rauscher, 1998) and music training bolsters this effect in both mathematics (Bilhartz, Bruhn, and Olson, 2000; Brothers, Shaw, and Wright, 1996; Costa-Giomi et al., 1999; Graziano, Peterson, and Shaw, 1999; Gromko and Poorman, 1998; Rauscher et al., 1997) and language (Douglas and Willatts, 1994; Ho, Cheung, and Chan, 2003).
In a meta-analysis of experimental studies on the relationship between spatial performance and music listening, Hetland (2000), from Harvard’s Project Zero, highlights significant limitations within existing studies. These include a reliance on quite small samples (ranging from 12 to 179 indi- viduals). Moreover, only one of the 20 studies reviewed was in a peer- reviewed journal and that particular study was an analysis of music majors in college, published more than a half-century ago. The remainder, which were never published and include seven doctoral dissertations (Vaughn and Winner, 2000), tend to focus singularly on low-SES or mid-SES individuals, thus constraining comparison, and few controls are included (Winner and Cooper, 2000a, 2000b). This is particularly important if the goal is to systematically assess if benefits of music involvement exist and how. Without doing so, the relation between music and intellectual development may be a spurious one.
Adolescence Using Three Measures of Music Participation
In another meta-analysis of experimental studies on the relationship be- tween spatial performance and music making, spanning the years between 1950 and 1999 (N 5 188), Hetland (2000) examined 14 comparable stud- ies. Although none were published in peer-reviewed journals, they do dem- onstrate a strong bivariate relationship between learning to play an instrument and spatial-temporal ability (median r 5 0.34; 25th quartile r 5 0.25; 75th quartile r 5 0.42; po0.001, two-tailed test). Findings were equivocal, however, as to the relationship between learning to play an
6 Social Science Quarterly
instrument and reading and mathematics achievement (Hetland and Win- ner, 2001). Indeed, there exists a relatively obvious social class bias in the methods used to measure these bivariate relations, as poor students have limited resources that may hinder music participation from the outset. Moreover, children from more well-to-do families, while perhaps more inclined to participate in music generally, are also advantaged in other ways meaningful to achievement (Bourdieu and Passeron, 1977; Downey, 1995a; Lareau, 2000, 2002; Teachman, 1987; DiMaggio, 1982). Without assessing social class variations, or controlling for other educational resources at chil- dren’s disposal, conclusions regarding the impact of music participation are tentative at best.
In an effort to remedy some of these limitations—particularly those per- taining to small sample sizes and potential social class variations—Catterall, Chapleau, and Iwanaga (1999:9–13) examine the influence of music par- ticipation on student math achievement using the National Educational Longitudinal Study (NELS:88). Comparing low-SES students who exhibit high math proficiency in 12th grade, 33 percent are involved with instru- mental music in the 10th grade, compared to 15 percent who are not involved. Yet, no inference of causality can be made as the positioning of students in the higher ranks could be due to other confounding factors. For example, the definition of music participation used by Catterall, Chapleau, and Iwanaga is the 10th-grade measure of participation in orchestra/band. If music participation positively affects cognition and some students who participate in the school band also participate in music outside of school, then they are advantaged. If students take music outside of school but do not participate in band, they are less advantaged, but more advantaged com- pared to students with no music participation. The music measure needs to be more precise but, given data limitations, it is not possible to control for the duration and quality of music participation. However, controlling for prior achievement would allow for a more precise comparison.
Broader analyses of extra-curricular involvement, such as that undertaken by Broh (2002), have added to our understanding of music’s potential correlation to achievement beyond possible direct cognitive effects, sup- porting the theory of cultural capital. Using the NELS:88 data, Broh studied an array of within-school extra-curricular activities (i.e., sports, cheerleading, drama, student council, yearbook, vocational clubs, and music) and found several associations between participation and achievement (grades and math and language scores). She shows this is due to garnering of social and cultural capital. Specifically, students who participate have more academ- ically-oriented peer groups, talk more with parents and teachers, and their parents are more likely to talk with friends’ parents. These benefits are more purely social in nature and may be important in countering lower self- esteem and locus of control. Students with early music instruction are more likely involved with other extra-curricular activities (Orsmond and Miller, 1999). Moreover, music participation at school has been shown to bolster
The Impact of Music on Childhood and Adolescent Achievement 7
not only individual benefits such as friendships with like-minded individuals and modeling commitment through rehearsals, but school music produc- tions are perceived as making a valuable contribution to social life through a widespread awareness of the show by nonparticipants (Pitts, 2007).
Importantly, serious music involvement often occurs outside of the school context—a fact seldom considered in prior work. As should be obvious from the discussion above, consideration of music’s impact necessitates (1) con- trols for potentially confounding factors; (2) a more longitudinal and rig- orous design that moves beyond bivariate relations and allows the researcher to capture temporal ordering; (3) consideration of variations in involvement by social class, race, and gender, for instance; and (4) a focus on the ways group disparities in music involvement might be contributing to the ac- ademic inequalities established in much prior research. Below, we specify several reasons why music participation may be meaningful for student academic achievement, how familial resources may play a role, and why disparities in music involvement and, thus, achievement, may exist across subgroups.
Music, Achievement, and the Potential for Inequality
Prior research has tested the cognitive effects of music participation with mixed results, although this literature has not tested the cultural impact of music as a mediating effect on achievement. Prior educational research has shown quite clearly a strong relationship between family background and student achievement, owing in part to institutional processes that advantage those of higher status. The investments families are or are not able to make are quite central in these regards. When children are provided with basic skills from the outset, but also continued investment in household educa- tional items and cultural capital, they enter the educational system and sorting process with clear-cut advantages (Astone and McLanahan, 1991; Alexander, Entwisle, and Thompson, 1987; Lareau, 2000; Kohn, 1959; Roscigno and Ainsworth-Darnell, 1999).
Though there is certainly discretion in educational investments (see Teachman, 1987), higher-SES and Caucasian parents have disparate re- sources available to invest relative to lower-status families (Roscigno, 1998). Sometimes, even within families, investments in cultural capital in particular can take on a gender-specific character (DiMaggio and Mohr, 1985; Buchmann, 2000). Music involvement may very well represent one such investment, impacted by prevailing stratification arrangements with impli- cations for educational success.
Lareau (2002), in one of the most developed and recent treatments of time use, shows how the investments of working-class and middle-class parents and families fundamentally differ in meaningful educational ways. Specifically, higher-SES parents tend to look at their children as ‘‘works in
8 Social Science Quarterly
progress’’ and structure their children’s time around furthering education outside of school. Music involvement and lessons may certainly be one such route. Lower-SES parents, in comparison, are less likely to structure their children’s time outside school in educationally important ways, regardless of race. If music involvement indeed reflects an important route through which resource and time investments are disparately allocated, and music itself influences achievement levels, then the issue of music involvement has clear- cut implications for our understanding of educational stratification. Indeed, this would be consistent with arguments pertaining to structure and the exclusionary nature of cultural reproduction (e.g., Bourdieu and Passeron, 1977; Roscigno and Ainsworth-Darnell, 1999).
Our analyses, following the discussion above, address two central ques- tions using a cultural capital framework. First, who participates in music both in and outside of school, and to what extent is such involvement stratified by social class, race/ethnic, and gender status? Second, and relative to the more central question discussed at the outset, do various forms of music involvement influence academic achievement, even after accounting for prior achievement, background statuses, and other educationally mean- ingful investments? Relatedly, to what extent might disparities in music involvement shape group-specific gaps in achievement that have been so well documented elsewhere?
Data and Measurement
We draw from two data sources collected by the Department of Edu- cation: the Early Childhood Longitudinal Study (ECLS-K) and the National Educational Longitudinal Study (NELS:88). ECLS-K was administered to approximately 20,000 U.S. kindergarten students in 1998–1999 from more than 1,000 schools, with follow-up waves in first, third, and fifth grade. We use the K–1st-grade data specifically, given the availability of music participation variables in these waves. NELS:88 followed a different group of students from eighth grade and beyond high school, with (high response rate) followups every two years. Its base year (1988) sample size is just under 25,000 adolescents from approximately 1,000 U.S. schools. We only draw on cases that include IRT (Lord, 1980) scores on math and reading. Given this and the sensitivity of longitudinal data to attrition, the samples are reduced in the latter waves, leaving a sample size of 4,376 in ECLS-K and a sample size of 7,781 in NELS:88. Both these data sources are nationally representative longitudinal studies utilizing multilevel stratified, clustered national probability samples. Proper weights are employed in our analyses, given subgroup over- and underrepresentations within each data set. These data are, in several regards, ideal, given relatively parallel indi- cators of achievement, music involvement, and student background over time.
The Impact of Music on Childhood and Adolescent Achievement 9
Achievement
Comparable measures of standardized achievement in reading and math- ematics are available in both data sets. Although standardized test scores are by no means perfect measures of cognition and cognitive complexity, they have proven to be relatively effective indicators of success in schooling. The standardized scores in the NELS:88, reported in Table 1, have a mean of 51 for both math and reading scores. For the ECLS-K, the reading mean is slightly higher at 57 and the mathematics score slightly lower at 44. We draw from later waves of NELS:88 (12th grade) and ECLS-K (first grade) for these dependent variables for reasons of temporal ordering. Family background, student status attributes, and controls for prior achieve- ment are measured during the base year (kindergarten and eighth grade, respectively).
Music Involvement
We include three parallel dichotomous measures of music involvement from each data set. Data limitations preclude a calibrated measure of par- ticipation. This is, however, a minor limitation given the validity of the large data sets and the large, representative samples. Formal music participation exists in and outside school and this is captured in both the childhood and adolescent data. Since there is significant variability nationwide in the extent and degree to which music classes are available, we first include an indicator of weekly, in-school music class participation.
One minor data limitation is that the data sets ask parallel music participation questions in the base year, but not consistently across subsequent waves. Therefore, the in-school music effect will be captured after participation occurred. To address this issue, we include an additional music participation question from the second wave (10th grade) of NELS:88 in our modeling of adolescent achievement. This measure of music participation captures, in half-year increments, the amount of in-school music coursework a student has taken between 8th and 10th grade. Unfortunately, the same measure was not included in the ECLS- K survey.
Notably, whereas nearly all small children are involved in a music lesson at least once a week, this only holds true for approximately half the adolescents sampled. This makes intuitive sense. By the high school years, music involvement becomes voluntary in terms of students’ curricular plan rather than a generic music class. Adolescents often have the option of taking band, orchestra, marching band, or, sometimes, chorus.
More pertinent, we believe, is the extent to which families invest in their children’s music involvement outside the parameters of school. Following Lareau (2003), such involvement (which requires both resources and time) may constitute educationally directed use of leisure time, particularly for higher-SES parents. In this vein, we include measures of music lessons
10 Social Science Quarterly
outside of school. Approximately 27 percent of adolescents and about 10 percent of small children were so engaged. We also include an indicator of parental musical involvement, in the form of attending concerts. This indicator likely captures not only household cultural capital in some generic
TABLE 1
Description of Key Measures, Mean, and Standard Deviation
ECLS-K NELS
Mean SD Mean SD
Mathematics Score Standardized reading IRT score
44.55 8.70 50.81 10.04
Music in school 44.65 8.62 51.66 10.05 Music outside school 44.97 8.72 52.73 10.00 Parent attend
concerts 44.72 8.72 51.77 9.98
Reading Score Standardized mathematics IRT score
57.07 13.00 50.59 9.89
Music in school 57.01 12.98 51.44 9.87 Music outside school 57.46 13.41 52.33 9.77 Parent attend
concerts 57.46 13.40 51.42 9.80
Music Involvement
In school Music in school, at least once a week
0.97 0.18 0.51 0.07
Outside school Music outside of school 5 1; no 5 0
0.10 0.29 0.27 0.07
Parent attend concerts
Parent attends concerts 5 1; no 5 0
0.40 0.49 0.63 0.07
Amount of music coursework
Coursework between 8th and 10th grades? (0.5 yr; 1 yr; 1.5 yrs; 2 yrs)
— 0.89 1.47
Family Background and Status Attributes
SES Socioeconomic status composite
0.05 0.74 0.00 10.86
Two parents 0.81 0.39 0.69 0.46 Single parent Coded yes 5 1; no 5 0 0.16 0.37 0.28 0.37 Neither parent Coded yes 5 1; no 5 0 0.03 0.16 0.03 0.17 Number of siblings Continuous variable 1.51 1.15 1.52 1.21 Female Coded yes 5 1; no 5 0 0.51 0.50 0.50 0.50 Black Coded yes 5 1; no 5 0 0.10 0.30 0.10 0.30 Hispanic Coded yes 5 1; no 5 0 0.09 0.29 0.12 0.33 Asian Coded yes 5 1; no 5 0 0.04 0.20 0.07 0.26 White Coded yes 5 1; no 5 0 0.76 0.42 0.70 0.45 More than 50 books Coded yes 5 1; no 5 0 0.72 0.45 0.71 0.30 Prior math
achievement Standardized base-year
mathematics IRT score 29.07 8.51 51.83 10.22
Prior reading achievement
Standardized base-year reading IRT score
33.63 10.53 51.56 10.01
The Impact of Music on Childhood and Adolescent Achievement 11
sense, but also the more general appreciation of music by parents and the likely introduction, appreciation, and use of music in the household.
Family Background, Status, and Controls
We also include baseline indicators of family background and race and gender status that much prior work has shown to be consistently influential for student achievement. These are nearly identical between the NELS:88 and ECLS-K samples and include, specifically, a composite of family so- cioeconomic status (SES), parental structure, race/ethnicity, gender, and if the family has more than 50 books in the home, a standard measure of cultural capital (DeGraaf, DeGraaf, and Kraaykamp, 2000). Our measure of 50 or more books was constrained by NELS:88, which coded the item dichotomously: Does your family have more than 50 books? We recoded the ECLS-K measure for comparison.
The SES composite was constructed by the Department of Education and includes income, parental level of education, and parental occupation. Family structure is measured discretely as living with two parents versus living with neither or only one, and we use the exact number of siblings present in the home. We include indicators of race/ethnicity, coded in dichotomous fashion, to assess potential effects of race on music involve- ment. There are too few Native Americans and Pacific Islanders in the sample; subsequently these cases were dropped. The referent in the following baseline models is a white male living in a two-parent family, either biological or blended.
Along with controls for household educational items such as books, we control throughout for baseline achievement levels at Time 1. Inclusion of such a control represents a serious effort to systematically isolate achieve- ment change over time and the extent to which music involvement affects achievement during early childhood years and adolescent years, respectively. All cases with missing data are removed from the analyses.
Analytic Strategy and Results
The reliance on these two large nationally representative data sets allows for a comparison between cohorts in terms of music participation and academic outcomes. It also advances the literature by allowing a more comprehensive analysis of the education process and how it interrelates with parental investment (i.e., music participation). This is important given that prior work has not addressed the determinants of music participation across cohorts.
Analyses proceed in two steps. We begin by addressing the question of who participates in music, and whether there are variations by social class,
12 Social Science Quarterly
Adolescence Using Three Measures of Music Participationrace, and gender status. For these models, we make use of logistic regression, and hold constant the number of books in the home as a control for other tangible educational investments. To the extent that class, race/ethnic, and gender differences exist, such differences may hold implications for differ- ences in achievement.
The second portion of our analysis examines the extent to which music participation may be meaningful for achievement. We undertake separate analyses for math and reading, and present childhood and adolescent models’ side by side for comparative purposes. Equation (1) is the baseline model of achievement with indicators of family background, student race and gender status, the number of books in the home, and prior achievement. Equation (2) introduces the three indicators of music involvement in an effort to assess both the impact on achievement as well as the extent to which music participation may be mediating some of the class, race, and gender effects highlighted in the first equation. For adolescent models, we include in a third equation 8th–10th-grade music coursework.
Music Involvement and Student Background
Table 2 reports logistic regression estimates of music involvement for children and adolescents by the status attributes of students and their fam- ilies, with a control for household educational resources in the form of number of books. The reader will first note that there appears to be no social class variation in within-school and external music involvement for children. Social class differences do, however, emerge for adolescents. Moreover, the effects of social class on parental music involvement are strong, statistically significant, and consistent for both small children and adoles- cents. Such effects are undoubtedly a function of variations in resource availability within families. In the case of music involvement occurring outside of school, resource advantages/disadvantages are also very likely compounded by differential structuring of children’s leisure time (Lareau, 2003). In general, family structure does not impact music involvement, with the exception of single-parent households, which depresses taking music in eighth grade, while having siblings seems to dilute resources, at least for adolescents.
Racial differences in music participation are a bit more complex. On average, African Americans, Hispanics, and Asians exhibit lower music involvement than whites. Asian students are more likely to take music outside of school as adolescents and black parents with young children attend more concerts than do whites. Children of color are significantly less likely to participate in all three as adolescents. Although the effects are more robust for adolescents, findings largely suggest an overall white advantage in music involvement during early childhood and the high school years. Gender effects are negligible to nonexistent, with the exception of the
The Impact of Music on Childhood and Adolescent Achievement 13
parents of young girls, who disproportionately attend concerts with their daughters.
Adolescence Using Three Measures of Music Participation
Clearly, attending concerts is, in part, a matter of economics, but it is also in keeping with Lareau’s description of the middle-class production logic of child rearing and is therefore culturally proscribed. Although certainly driven by resource disparities, and family SES in particular, there is a discretionary dimension to educational investments—investments that may take multiple forms, from tangible resources to the structuring of leisure time in ways that may be educationally meaningful. By high school, how- ever, some students earn an income and support their own interests, such as music lessons and playing in bands. The structuring of leisure time is not only determined by guardians but by students, suggesting culture weighs heavy in the decision to participate in music. Unfortunately, current data do not query both parental and student levels of music interest or preference, which would permit a direct measure of intergenerational cultural impact. Instead, the data provide proximate measures of cultural capital and direct measures of achievement.
TABLE 2
Binary Logistic Regression Coefficients of SES, Family Structure, Race, Gender, and Cultural Capital on Music Involvement by Children (C) and Adolescents (A)
Music Inside of School
Music Outside of School
Parental Music Involvement
C A C A C A
SES 0.14 0.09 n n n 0.09 0.34 n n n 0.33 n n n 0.34 n n n
(0.13) (0.03) (0.07) (0.03) (0.05) (0.03) Single parent �0.08 �0.10 n 0.26 �0.03 �0.10 �0.01
(0.23) (0.05) (0.14) (0.05) (0.09) (0.05) Neither parent �0.36 0.12 0.19 0.18 �0.04 0.10
(0.42) (0.14) (0.32) (0.16) (0.20) (0.14) Number of siblings �0.15 �0.04 n n 0.07 �0.12 n n n �0.00 �0.12 n n n
(0.08) (0.01) (0.04) (0.01) (0.03) (0.01) Black �0.78 n n �0.30 n n n �0.39 n �0.28 n n 0.28 n n �0.16 n
(0.26) (0.07) (0.20) (0.09) (0.12) (0.08) Hispanic �0.07 �0.81 n n n �0.11 �0.67 n n n 0.06 �0.76 n n n
(0.30) (0.07) (0.18) (0.09) (0.11) (0.07) Asian 0.25 �0.29 n n n �0.55 0.22 n 0.39 �0.51 n n n
(0.53) (0.08) (0.30) (0.09) (0.16) (0.08) Female 0.13 �0.03 0.07 �0.05 0.17 n n �0.08
(0.17) (0.04) (0.10) (0.05) (0.06) (0.04) More than 50 books 0.06 0.11 �0.21 0.04 0.42 n n n 0.07 n n
(0.20) (0.07) (0.12) (0.09) (0.08) (0.07)
npo0.05; n npo0.01; n n npo0.001, two-tailed test.
14 Social Science Quarterly
Adolescence Using Three Measures of Music Participation
Adolescence Using Three Measures of Music Participation
RUBRIC
Excellent Quality
95-100%
Introduction 45-41 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Literature Support
91-84 points
The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned.
Methodology
58-53 points
Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met.
Average Score
50-85%
40-38 points
More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided.
83-76 points
Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration.
52-49 points
Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met.
Poor Quality
0-45%
37-1 points
The background and/or significance are missing. No search history information is provided.
75-1 points
Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration.
48-1 points
There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met
You Can Also Place the Order at www.collegepaper.us/orders/ordernow or www.crucialessay.com/orders/ordernow