The Impact of Music on Childhood and
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
Direct correspondence to Darby Southgate, Department of Sociology, The Ohio State
University, 238 Townshend Hall, 1885 Neil Ave. Mall, Columbus, OH 43210 hSouth-
firstname.lastname@example.org. 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
r2009 by the Southwestern Social Science Association
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).
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
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
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
In another meta-analysis of experimental studies on the relationship be-
tween spatial performance and music making, spanning the years between
1950 and 1999 (N5188), 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 r50.34; 25th quartile
r50.25; 75th quartile r50.42; 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
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
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
The Impact of Music on Childhood and Adolescent Achievement 9
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,
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
Description of Key Measures, Mean, and Standard Deviation
Mean SD Mean SD
Mathematics Score Standardized reading IRT
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
44.72 8.72 51.77 9.98
Reading Score Standardized mathematics
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
57.46 13.40 51.42 9.80
In school Music in school, at least
once a week
0.97 0.18 0.51 0.07
Outside school Music outside of
school 51; no 50
0.10 0.29 0.27 0.07
concerts 51; no 50
0.40 0.49 0.63 0.07
Amount of music
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
0.05 0.74 0.00 10.86
Two parents 0.81 0.39 0.69 0.46
Single parent Coded yes 51; no 50 0.16 0.37 0.28 0.37
Neither parent Coded yes 51; no 50 0.03 0.16 0.03 0.17
Number of siblings Continuous variable 1.51 1.15 1.52 1.21
Female Coded yes 51; no 50 0.51 0.50 0.50 0.50
Black Coded yes 51; no 50 0.10 0.30 0.10 0.30
Hispanic Coded yes 51; no 50 0.09 0.29 0.12 0.33
Asian Coded yes 51; no 50 0.04 0.20 0.07 0.26
White Coded yes 51; no 50 0.76 0.42 0.70 0.45
More than 50 books Coded yes 51; no 50 0.72 0.45 0.71 0.30
mathematics IRT score
29.07 8.51 51.83 10.22
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
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
race, 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
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
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.
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
Music Outside of
CACA C A
SES 0.14 0.09
(0.13) (0.03) (0.07) (0.03) (0.05) (0.03)
Single parent 0.08 0.10
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
(0.08) (0.01) (0.04) (0.01) (0.03) (0.01)
(0.26) (0.07) (0.20) (0.09) (0.12) (0.08)
Hispanic 0.07 0.81
(0.30) (0.07) (0.18) (0.09) (0.11) (0.07)
Asian 0.25 0.29
(0.53) (0.08) (0.30) (0.09) (0.16) (0.08)
Female 0.13 0.03 0.07 0.05 0.17
(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
(0.20) (0.07) (0.12) (0.09) (0.08) (0.07)
po0.001, two-tailed test.
14 Social Science Quarterly
The Association Between Music and Achievement
Music indeed appears to matter. Tables 3 and 4 report regression esti-
mates of math and reading achievement for childhood and adolescent sam-
ples. The ﬁrst equation, our baseline model, introduces measures of family
SES and structure, race and gender, and controls for educational items and
prior achievement (eighth grade for adolescents; kindergarten for children).
OLS Regression Coefﬁcients and SEs of SES, Family Structure, Race, Gender,
Music Involvement, Cultural Capital, and Prior Achievement on Mathematic
IRT Scores for Children (C) and Adolescents (A)
Model 1 Model 2
(0.13) (0.15) (0.13) (0.15)
Single parent 0.33 1.60
(0.24) (0.23) (0.24) (0.24)
Neither parent 1.13
(0.51) (0.75) (0.50) (0.83)
Number of siblings 0.02 0.25
(0.08) (0.07) (0.08) (0.07)
Black 0.18 2.06
(0.31) (0.37) (0.31) (0.39)
(0.30) (0.35) (0.30) (0.37)
Asian 0.23 0.11 0.27 0.15
(0.65) (0.43) (0.65) (0.44)
Female 0.13 1.00
(0.17) (0.21) (0.17) (0.22)
Music in school — — 1.82
Music outside school — — 0.47 0.44
Parents attend concerts — — 0.35
Amount of music coursework — — — 0.50
More than 50 books 0.89
(0.19) (0.36) (0.21) (0.38)
Prior achievement 0.73
(0.01) (0.01) (0.01) (0.01)
Constant 22.94 48.49 21.19 48.64
(0.40) (0.73) (0.57) (0.76)
0.60 0.23 0.60 0.23
po0.001, two-tailed test.
The Impact of Music on Childhood and Adolescent Achievement 15
All background indicators act as one would expect, and in statistically sig-
nificant ways, for both reading and math. Notable is the strong effect of SES
even with controls from prior achievement. It is clearly the case that SES,
and the advantages/disadvantages it affords, is not purely inﬂuential by
shaping baseline achievement levels; rather, its impact persists into the
OLS Regression Coefﬁcients and SEs of SES, Family Structure, Race, Gender,
Music Involvement, Cultural Capital, and Prior Achievement on Reading
IRT Scores for Children (C) and Adolescents (A)
Model 1 Model 2
(0.20) (0.15) (0.20) (0.16)
Single parent 0.76
(0.36) (0.24) (0.38) (0.25)
Neither parent 2.48
(0.78) (0.78) (0.78) (0.86)
Number of siblings 0.31
(0.12) (0.07) (0.12) (0.07)
(0.47) (0.38) (0.47) (0.40)
Hispanic 0.39 0.18 0.43 0.17
(0.48) (0.36) (0.48) (0.38)
0.30 1.87 0.25
(0.95) (0.44) (0.95) (0.45)
(0.24) (0.21) (0.26) (0.22)
Music in school — — 2.12
Music outside school — — 0.44 0.62
Parents attend concerts — — 0.10 0.02
Amount of music coursework — — — 0.44
More than 50 books 1.20
(0.32) (0.37) (0.33) (0.39)
Prior achievement 0.86
(0.01) (0.01) (0.01) (0.01)
Constant 27.23 46.61 51.01 46.80
(0.57) (0.75) (0.89) (0.78)
0.57 0.16 0.58 0.16
po0.001, two-tailed test.
16 Social Science Quarterly
African-American students remain disadvantaged in terms of both math
and reading achievement in these models, while the disadvantage for His-
panic students only exists for childhood math. Asian adolescents do not
differ significantly from white adolescents with prior achievement included
in the models. Among younger Asian children, however, we ﬁnd an ad-
vantage in reading. Females generally exhibit lower math achievement than
do their male counterparts, but significantly higher reading achievement. As
expected, household educational items have a positive effect for both age
groups and for both achievement outcomes.
Equation (2) introduces our indicators of music involvement. For reading
achievement, music involvement within school positively predicts achieve-
ment for both adolescent and small children. It may be the case that there is
generally greater variation in reading ability among small children, and that
active involvement of children in music contributes in some way to the
garnering of early reading skills. Music participation outside of school is
positively associated with reading achievement for adolescents. This effect
remains even when in-school music is controlled. However, parental music
involvement is not significantly associated with reading achievement. Even
more notable is that these effects emerge even when other household
educational items and especially prior achievement are accounted for. Math
performance is associated with music participation in school and parental
attendance at concerts for young children, and a robust effect unfolds when
music participation has occurred recently in adolescents.
The results thus far suggest unique and robust associations between
achievement and music—effects that are not strictly tied to very early cog-
nitive development but that, rather, take place during the early and later
schooling years. All three forms of music involvement matter for adolescents
and this holds true for reading and less so math achievement. For small
children, the clear beneﬁt of music involvement on math achievement
is found in school and parental music participation, but not in outside of
school participation. For reading, music in school translates into higher
overall reading achievement. Again, we would stress that younger children
are nearly universally placed in music classes whereas adolescents choose to
participate and few families choose music lessons outside of school for young
Does music involvement add to our understanding of academic achieve-
ment? The answer is both yes and no. On the one hand, music clearly
matters for achievement in statistically meaningful ways as denoted in the
ﬁndings just presented. The reader will note, however, that the overall vari-
ance explained changes little across equations as music indicators are added.
This suggests to us that music is meaningful not as a predictor of achieve-
ment in and of itself, but rather as a mediator, to some degree, of family
background and student status, thus supporting arguments and theorizing
pertaining to cultural capital. Music, for example, might inﬂuence dispo-
sition or habits of mind. Our earlier modeling in Table 2 established the
The Impact of Music on Childhood and Adolescent Achievement 17
ways music involvement varies systematically as a function of social class,
race/ethnicity, and, to a lesser extent, gender. Those patterns, combined with
changes in coefﬁcient magnitudes for SES, race/ethnicity, and gender across
equations of Tables 3 and 4, strongly support this possibility, as do sup-
plemental analyses that, due to space constrains, are not reported in the
tables. Comparing the coefﬁcients for SES across Equations (1) and (2),
without the interaction terms, we see a decline of approximately 3 percent
for math, less so for reading. Similar, albeit small, declines can be seen for
measures of race/ethnicity and gender.
Prior research has attempted to measure the impact of music involvement
on student achievement. Limitations in research designs, however, have left
many questions unanswered. In this article, we have attempted to overcome
some prior limitations by examining three dimensions of music involvement
and variations by student status, by controlling for prior achievement, thus
isolating potential effects, and by comparing such effects across unique
samples of small children and adolescents. Only a randomized design
experimental study can capture causality; yet our analyses demonstrate in a
relatively rigorous fashion a robust relationship between music participation
and achievement—a relationship that emerges particularly when music
participation is conceptualized and measured broadly. Most children are
probably involved in classical music and we do not have measures of
countercultural or pop music nor do we know how many students are in
bands outside school. We would expect to see more robust ﬁndings if
participation could be more precisely calibrated.
Notably, we found evidence of social class variation in within-school
music involvement in adolescents but not in early childhood. The effects
of class on parental music involvement were strong and consistent for
both samples. We believe that this pattern is at least partially a function of
resource inequalities, which, if anything, only exacerbate social class differ-
ences in how children’s leisure time is structured (Lareau, 2003). As a
mediator of educational outcomes, music involvement holds significance for
both math and reading achievement. Music participation generally increases
achievement levels, although gains are not distributed equally among all
students. A white student advantage exists in music involvement during early
childhood and the high school years. As noted above, there is certainly a
social class bias in these processes.
Admittedly, our data and analyses are limited in their ability to measure
and capture the quality and duration of children’s and adolescents’ partic-
ipation. Although our study captured the inﬂuence of music involvement
and different types of involvement in a manner unique to the literature,
future data-collection efforts and analyses should consider quality and du-
18 Social Science Quarterly
ration. Moreover, to gauge the relevant microinteractional processes that are
involved would arguably require more in-depth, perhaps case-speciﬁc,
analyses of what music participation means for families and social groups of
varying statuses. Music involvement is a form of cultural capital that seems
to provide cognitive and social tools that help students successfully navigate
the educational terrain. Clearly, more work on this topic is warranted. Our
analyses are but an important starting point.
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