1

Motivational Attributions of Second Grade Music Students

Alex J. Boccio

The College of Saint Rose

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I. Introduction

Educators have long been concerned with motivation.

Understanding motivation may help students reach a higher

level of academic achievement (Weiner, 1979). Student

achievement motivation has been studied substantially in

education (Bar-Tal, 1978; Frieze & Snyder, 1980; Medway &

Lowe, 1980; Nicholls, 1976). Music education researchers

have also studied motivation to investigate what students

believe to be the causes of their success or failure in

music (Asmus, 1985; Legette, 1998; Reimer, 1975).

Categorizing student attributions of their success and

failure at a task led to the development of Attribution

Theory (Asmus, 1986a). Weiner (1972) first used Attribution

Theory to classify students’ beliefs of success and failure

at achievement tasks using a two-dimensional model. The two

framework dimensions were locus of control and stability.

Locus of control, as defined by Weiner, was the belief that

3

behaviors were caused by internal or external factors.

Stability was defined as no change over time. This dimension

was divided into stable and unstable through time. The four

attributions identified by the two-dimensional model were

ability, task difficulty, luck, and effort. Weiner revised

the classification system, adding a third dimension. The

supplementary dimension was controllability, which was

divided into whether the cause was within or outside the

learner’s control. The eight attributions identified by the

three-dimensional model are ability, task difficulty, luck,

mood, typical effort, immediate effort, teacher bias, and

unusual help (Weiner, 1979). Attribution Theory suggested

that what a student believes to cause success or failure in

a task will affect how that task is approached (Asmus,

1985).

In music education, Asmus (1985) researched Attribution

Theory in connection with students. Subjects surveyed

included 118 sixth grade general music students from three

different schools of varied socioeconomic status. Responses

were collected on special lined forms during their intact

4

general music class. Learners were asked to give five

reasons why some students do well in music, and five reasons

why some students do not do well in music. Responses were

analyzed and sorted into one of the four attribution

categories in Weiner’s 1972 model. The internal

attributions, ability and effort, saw the highest frequency

of response for success and failure in music.

In a more extensive study, Asmus (1986b) investigated

the causal beliefs for success and failure in fourth through

twelfth grade music students. The survey form was very

similar to the previous study, but added items to collect

information on grade and gender. The survey was given to 589

subjects from eight different schools of varied

socioeconomic status. All subjects were enrolled in

instrumental, vocal, or general music classes. The surveys

were administered during regular meeting times, and

sufficient time was given to complete the form. Internal

causes, ability and effort, for success and failure were

cited 80 percent of the time. In addition, as grade-level

increased, the number of internal-stable attributions,

5

namely ability, increased (Asmus, 1986b). The research

suggested that Weiner’s Attribution Theory models were not

germane to music education because of the uneven

distribution of attributions (Asmus, 1986a).

           A study by Legette (1993) examined what third and

fourth grade students attribute to their success and failure

in music. This study used 261 subjects from two public

schools. The identified schools served a majority of

students who come from low socioeconomic status. Students

were administered Asmus’ (1986a) Music Attribution

Orientation Scale (MAOS), see Appendix A, during regular

music lessons. This scale was used because of the relevance

to music. The MAOS consisted of 35 items divided into five

sections. The five subscales were effort, background,

classroom environment, musical ability, and affect for

music. The MAOS described affect for music as the enjoyment

of listening and participating in music. Subjects indicated

the importance of each item on a scale from one to five,

with five being extremely important and one being not

important at all. The results indicated that ability and

6

effort attributions were most frequently cited. Third grade

subjects, n = 146, placed more importance on background,

class environment, and affect for music than higher grade

levels (Legette, 1993).

Legette (1998) expanded the previous examination by

including middle and high school learners, and a larger

sample size. Subjects were 1,114 students enrolled in two

neighboring schools, a city school with a majority of black

students and a county school with a majority of white

students. The learners were given Asmus’ (1986a) MAOS during

their weekly music lessons. Results showed that internal

causes, ability and effort, were the most important

attributions overall. However, students of the county school

attributed classroom environment as the most important cause

for success and failure in music. Research suggested that

race might have contributed to the difference (Legette,

1998).

While studies have examined the correlation between

Attribution Theory and musical achievement motivation for

third through twelfth grade students (Asmus, 1985, 1986b;

7

Legette, 1993, 1998) there is a lack of research relating

Attribution Theory to second grade music students. This

investigation may benefit music educators, informing them of

second grade students’ attributions of success and failure

in music. With this, educators may employ strategies to

motivate these learners to achieve musically. The purpose of

this investigation was to examine motivation variables of

second grade music students.

1.     What variables do second grade students cite as most

important for success or failure in music?

2. Does socioeconomic status impact the variables cited

as most important?

3. Does ethnicity impact the variables cited as most

important?

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II. Related Literature

The purpose of this investigation was to examine

motivation variables of second grade music students. The

specific research questions addressed in this study were

(1) what variables do second grade students cite as most

important for success or failure in music; (2) does

socioeconomic status impact the variables cited as most

important; and (3) does ethnicity impact the variables cited

as most important? The present study investigated topics

which included attribution models, importance of

attributions, effects of socioeconomic status on achievement

motivation, and effects of ethnicity on achievement

motivation.

In Attribution Theory, Weiner developed models that

illustrated the attributions believed to be associated with

educational motivation. According to Attribution Theory,

achievement motivation is effected by the student’s

perception of the task. How similar tasks are approached in

the future is determined by the learners’ believed causes of

success or failure (Weiner, 1972). Weiner’s first conception

9

of Attribution Theory to categorize students’ beliefs of

success or failure at a task used two dimensions, locus of

control and stability. Locus of control was defined as

behaviors that were caused by internal or external factors.

Stability was defined as the dearth of change over time. An

attribution could be defined as either stable or unstable

through time. The four attributions exemplified in this

early model were ability, task difficulty, luck, and effort.

Weiner (1979) revised his classification system adding a

third dimension, controllability, which was divided into

whether the cause was within or outside the learner’s

control. The eight attributions identified by the three-

dimensional model are ability, task difficulty, luck, mood,

typical effort, immediate effort, teacher bias, and unusual

help.

The Music Attribution Orientation Scale by Asmus

(1986a) was developed as an attribution model specific for

music education. The development of the scale came from

prior research by Asmus (1985). Students were given lined

paper to indicate why some students succeed in music, and

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reasons why some students fail in music. Results determined

that there was an imbalance in the attributions cited from

Weiner’s (1972) model. The internal attributions, effort and

ability received the majority of attributions cited. Asmus’

(1986a) scale was divided into five subscales which were

effort, background, classroom environment, ability, and

affect for music.

The importance of motivational attributions has been

researched extensively in education. Nicholls (1976)

evaluated student responses to perceptions of effort and

ability. The purpose of the study was to evaluate responses

to imagined task outcomes. Subjects were 200 college

students, given a questionnaire that asked about specific

scenarios and the effects it would have. Subjects indicated

that they would feel more pride in the success of a task, as

well as less shame in the failure of a task, if sufficient

effort were given.

A study by Bar-Tal (1978) investigated the educational

research of achievement related behaviors. The research

suggested that educators should emphasize ability and effort

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as causes of success, and lack of effort as the primary

cause of failure to maximize learners’ academic performance.

Deiner & Dweck (1978) examined the cognitive and

motivational differences of subjects who had a wide range of

achievement. Subjects who were classified as helpless cited

uncontrollable variables as reasons for failure, such as

lack of ability. Subjects classified as mastery-oriented

cited more effort variables as a cause for success or

failure at a task.

Medway and Lowe (1980) examined the responses of 122

subjects in a cross-aged tutoring program regarding

motivational attributions and performance. The purpose of

this study was to compare attributions made for tutoring

outcomes prior to and during tutoring programs. Both tutors

and tutees indicated that learning was more dependant on

effort, rather than ability, when attributions were measured

at different times of the tutoring process.

A study by Frieze and Snyder (1980) interviewed first,

third, and fifth grade students, collecting their beliefs of

success or failure in four academic and non-academic

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activities. The four activities were taking an academic

test, completing an art project for class, playing football,

and catching frogs. Attributions differed across the

situations. Effort was the most important cause for success

or failure in an academic testing situation.

Anderson and Jennings (1980) investigated the effects

attributing initial failure to ineffective strategies on

performance expectancies. The results suggested that

subjects who attribute task outcomes to controllable

factors, such as strategy, would later attribute this effort

to their success. This differed from subjects who attributed

initial failure to lack of ability, an uncontrollable

variable. These subjects believed that they would not be

able to improve in performance.

Ames and Archer (1988) investigated how motivational

processes are related to mastery and performance goals in

classroom settings. Subjects were 176 junior and senior high

school students from a school for the academically advanced.

Subjects were randomly selected from one of their classes to

respond to a questionnaire about classroom goals, effective

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learning strategies, and their attitudes towards task

completions. Students who emphasized mastery goals reported

more effective task completion strategies, preferred

challenging tasks, enjoyed the class more, and felt that

their effort would bring them success. Subjects that

perceived performance goals as most important cited ability

causes to their academic success.

In music education, Reimer (1975) examined the

influence of subjects’ contributing attributions for music

achievement. Subjects were 128 undergraduates participating

in a piano practicum received instructions describing

successful piano performance in terms of ability, effort,

task difficulty or luck. All subject received feedback that

they were successful. The results showed that subjects who

received internal attribution instructions, such as effort

or ability feedback, reported a more positive effect than

those receiving external attribution instructions, such as

task difficulty and chance.

Asmus (1985) researched Attribution Theory in

connection with music students. Subjects surveyed included

14

118 sixth grade general music students in intact classrooms

from three different schools of varied socioeconomic status.

Responses were collected on special lined forms during their

general music class. Learners were asked to give five

reasons why some students do well in music, and five reasons

why some students do not do well in music. Responses were

analyzed and sorted into one of the four attribution

categories in Weiner’s 1974 model. The internal

attributions, ability and effort, saw the highest frequency

of response for success and failure in music.

In a more extensive study, Asmus (1986b) investigated

the beliefs for success and failure in fourth through

twelfth grade music students. The survey form was very

similar to the previous study, but added items to collect

information on grade and gender. The survey was given to 589

subjects from eight different schools of varied

socioeconomic status. All subjects were enrolled in

instrumental, vocal, or general music classes. The surveys

were administered during regular meeting times, and

sufficient time was given to complete the form. Internal

15

causes, ability and effort, for success and failure were

cited 80 percent of the time. In addition, as grade-level

increased, the number of internal-stable attributions,

namely ability, increased. The research suggested that

Weiner’s Attribution Theory models were not germane to music

education because of the uneven distribution of attributions

(Asmus, 1986a).

Asmus (1986) also researched undergraduate students.

Subjects were 143 enrolled in music education and music

therapy programs. Results showed that there was a difference

between attributions when discussing personal success or

failure and other’s success and failure. Results showed that

task difficulty was attributed to personal success and

failure, and effort was attributed to other’s success or

failure.

Chandler, Chiarella, and Auria (1988) researched high

school instrumental music students’ performance expectancy,

success, and instrument satisfaction. The purpose of this

study was to determine student motivation factors in band.

Subjects were 234 high school band students. Subjects were

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given a questionnaire to determine the sample demographics,

and determine attributional causes of motivation. The

results suggested that students who chose their instrument

again were satisfied with their performance level. In

addition, internal attributions, such as ability and effort

were the most important variables for successful

performance.

Vispoel and Austin (1995) examined 211 junior high

school music students. The investigation looked at what

attributions seventh and eighth graders cited, and if there

were differences between genders. A questionnaire of 105

items was administered to collect demographic information

and success or failure attributions. Results showed that

students cited internal causes for success, and external

causes for failure. In addition, there were significant

differences in attribution citations, such as effort, due to

grade level and gender.

In a more specialized study, Austin and Vispoel (1998)

administered 261 seventh graders Asmus’ (1986a) Music

Attribution Orientation Scale and Magnitude of Motivation.

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The results suggested that, in comparison with previous

research (Vispoel & Austin, 1995), attributions change as

students get older. Further, attributional beliefs

concerning ability were strongly linked to the learners’

self-concept of music and music achievement test scores.

A study by Legette (1993) examined what third and

fourth grade students attribute to their success and failure

in music. This study used 261 subjects from two public

schools. The identified schools served a majority of

students who came from low socioeconomic status. Subjects

were administered Asmus’ (1986a) Music Attribution

Orientation Scale (MAOS) during regular music lessons. This

scale was used because of the relevance to music. The MAOS

consisted of 35 items divided into five sections. The five

subscales were effort, background, classroom environment,

musical ability, and affect for music. The MAOS described

affect for music as the enjoyment of listening and

participating in music. Subjects indicated the importance of

each item on a scale from one to five, with five being

extremely important and one being not important at all. The

18

results indicated that ability and effort attributions were

most frequently cited. Third grade subjects, n = 146, placed

more importance on background, class environment, and affect

for music than higher grade levels (Legette, 1993).

Legette (1998) expanded the previous examination by

including middle and high school learners, and a larger

sample size. Subjects were 1,114 students enrolled in two

neighboring schools, a city school with a majority of black

students and a county school with a majority of white

students. The learners were given Asmus’ (1986a) MAOS during

their weekly music lessons. Results showed that internal

causes, ability and effort, were the most important

attributions overall. However, students of the county school

attributed classroom environment as the most important cause

for success and failure in music. The data suggested that

race might have contributed to the difference, but this

statement was speculative and must be approached with

caution.

Studies in music achievement motivation (Asmus, 1985,

1986; Legette, 1998) partially address socioeconomic status.

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Although these studies mention school setting, there is a

dearth of supportive data, making these views speculative,

and should be approached with caution. Socioeconomic status,

according to Conger, Ge, Elder, Lorenz, & Simons (1994) is

the level of economic pressure in which material needs are

met, debts are paid, and expenses are managed to live within

a mean.

Ginsburg and Bronstein (1993) examined the relationship

between socioeconomic status and motivation. Family and

parent measures were collected from ninty-three fifth-grade

subjects. Results showed that learners from low

socioeconomic status do poorer academically, are rated as

less intrinsically motivated, and rely on more external

sources of motivation.

Marjoribanks (1986) researched Australian high school

adolescents to determine their sources of motivation

relating to social class. Subjects were 512 Australian

adolescents who were administered questionnaires collecting

demographic, and aspiration information. Results suggested

that middle class adolescents attributed motivation to their

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attitudes towards school and specific subjects. However,

lower class adolescents reported more parental influences

for motivation.

Oysterman, Harrison, & Bybee (2001) conducted an

investigation to determine if racial identity has a negative

effect on academic efficacy, the belief that one can succeed

at academic tasks. Subjects included 92 African American

eighth graders from a high-poverty school. Questionnaires

were administered in the fall and spring, containing items

on academic efficacy, racial identity, and self-reported

grades. Results suggested that high levels of racial

identity had strong implications for motivation, academic

achievement, and academic self-concepts. These implications

effected subjects academic motivation, achievement, and

self-concept negatively.

Banskton and Zhou (1997) investigated how cultural

identity plays a role in one’s social relationships. Subject

surveyed were 402 Vietnamese Americans enrolled in the ninth

through twelfth grades. The questionnaire collected

demographic data and information on social relationships.

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The results suggested that subjects with a closer social

embeddedness to Vietnamese cultures did better in school

because of the promotion of academics. Conversely,

Vietnamese American adolescents who identified more closely

with mainstream American culture had lower academic

achievement.

A study by Eaton and Dembo (1997) investigated the

differences in motivational beliefs between Asian American

and Non-Asian ninth grade students. Subjects included

154 Asian American students and 372 Non-Asian students.

Subjects answered a questionnaire about their academic

beliefs and completed an academic task to assess achievement

behavior. The results suggested the Asian American students

had lower academic self-efficacy, however they performed

significantly better on the academic achievement task. It

was suggested that Asian American’s fear of consequence due

to academic failure best explained their performance.

Overall, the research suggested that motivational beliefs

elicit different responses in different ethnic groups.

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III. Method

Subjects were N = 1,010 second grade students enrolled

in intact general music classes from sixteen schools, School

1 n = 54, School 2 n = 50, School 3 n = 82, School 4 n = 56,

School 5 n = 58, School 6 n = 49, School 7 n = 76, School 8

n = 79, School 9

n = 63, School 10 n = 51, School 11 n = 78, School 12 n =

46, School 13 n = 67, School 14 n = 70, School 15 n = 62,

and School 16 n = 69.

Socioeconomic background data for each school was

collected based on district economic disadvantage

percentages determined by state enrollment data reports,

which were 26%, 63%, 42%, 46%, 42%, 47%, 14%, 14%, 7%, 7%,

7%, 72%, 72%, 83%, 83%, and 83%, respectively. Subjects were

divided into three levels of socioeconomic status (SES),

which were high SES n = 347, middle SES n = 299, and low SES

n = 364.

Subjects also represented the following heritages and

ethnic backgrounds, Non-Hispanic White or Euro-American n =

724, Hispanic or Latino n = 84, Black or African American n =

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121, and Asian n = 81. For a more accurate statistical

comparison, smaller populations were combined. This

investigation looked at the difference between White

n = 724 and Non-White n = 286 subjects. Students with

disabilities, as well as English language learners, were

included in this investigation. A pilot study with n = 104

subjects of a similar demographic was conducted to assess

the data collection procedure.

Subjects were administered Asmus’ (1986a) Music

Attribution Orientation Scale (MAOS) during regular class

meeting times. This scale was chosen because of the

relevance to music, and as a comparison to previous research

(Austin & Vispoel, 1998; Legette, 1993, 1998). The MOAS

consisted of thirty-five items divided into five sections.

The five subscales were effort, background, classroom

environment, musical ability, and affect for music. There

were seven items corresponding to each subscale. Subjects

indicated the importance of each item on a scale from one to

five with five meaning extremely important to one meaning

not important at all. A cover page was attached to the MOAS

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to collect ethnic demographic information. The assessment

was administered in accordance with subjects’ Individualized

Education Programs and Section 504 plans. The directions for

the MAOS were read aloud by a recording of the researcher,

and each item was read twice. Based on subjects’ needs,

breaks were provided at determined intervals between

sections. A mean score and standard deviation were developed

for each subscale. This determined which variables were

believed to be most important. A

two-way multivariate analysis of variance (MANOVA)

determined the relationships between subjects the two

different race groups, and three different levels of

socioeconomic status.

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IV. Results

A mean score and standard deviation was developed for

each of the five subscales. This determined which variables

were believed to be most important. A

two-way multivariate analysis of variance determined the

relationships between subjects of the two race groups, and

three different levels of socioeconomic status. The

reliability for all subject answers, calculated by

Cronbach’s Alpha Reliability, was .897.

The first research question examined which subscale

variables from Asmus’ (1986b) Music Attribution Orientation

Scale were most attributed to success or failure in music

(see Table 1). The means and standard deviations

respectively for all subject responses with each subscale

were effort (4.16, .65), background (2.96, 1.10), classroom

environment (3.98, .90), musical ability (3.70, .82), and

affect for music (3.03, 1.21). Subjects cited effort, with a

mean score of 4.16, as the most important attribution,

followed by classroom environment, with a mean score of

3.98.

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Table 1A Comparison of the Means and Standard Deviations of the Five Subscales

EffortSubscal

e

Background

Subscale

ClassroomEnvironme

ntSubscale

MusicalAbilitySubscal

e

Affectfor

MusicSubscal

eMean 4.16 2.96 3.98 3.70 3.03

StandardDeviation .65 1.10 .90 .82 1.21

In comparison with previous research (Asmus, 1985,

1986c; Legette, 1993, 1998), second grade music students

cite different attributions as most important than students

in more advanced grade levels. One possible reason for the

discrepancy is the developmental and academic immaturity of

the subjects examined. Overall, second grade subjects may

have lower academic ability than more advanced grades. It is

possible that the subjects did not understand the task of

completing the scale, due to their language and vocabulary

limitations. In addition, second grade subjects do not hold

high levels of academic self-regulation, the process of

turning cognitive ability into academic skill. Metacognition

and the ability to attribute a cause to an effect are not

27

simple tasks for this age, which may have affected the mean

scores (McClelland, Morrison, & Holmes, 2000).

The second research question investigated whether

socioeconomic status impacted the variables cited as most

important. The independent variables for the two-way

multivariate analysis of variance were socioeconomic status

and ethnic group. The dependant variables for the MANOVA

were the five subscales from Asmus’ (1986a) MAOS. The

descriptive statistics for the independent and dependent

variables used in the two-way MANOVA are presented in Table

2.

Table 2Descriptive Statistics for Socioeconomic Status and Ethnicity on the Five

SubscalesMAOS

SubscalesSocioeconomi

cStatus

EthnicGroup Mean

StandardDeviatio

n NEffort High SES Whites 4.05 .66 304

Non-Whites

3.78 .81 43

Total 4.02 .69 347Middle SES Whites 4.02 .69 285

Non-Whites

4.07 .68 14

Total 4.02 .69 299Low SES Whites 4.33 .54 135

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Non-Whites

4.45 .41 229

Total 4.41 .47 364Total Whites 4.09 .66 724

Non-Whites

4.33 .56 286

Total 4.16 .65 1010Background High SES Whites 2.70 1.04 304

Non-Whites

2.66 1.14 43

Total 2.69 1.05 347Middle SES Whites 2.70 1.05 285

Table 2 (cont.)Descriptive Statistics for Socioeconomic Status and Ethnicity on the Five SubscalesMAOS Subscales Socioeconomi

cStatus

EthnicGroup

Mean StandardDeviatio

n

N

Non-Whites

2.69 1.05 14

Total 2.70 1.05 299Low SES Whites 3.21 1.08 135

Non-Whites

3.53 .97 229

Total 3.41 1.02 364Total Whites 2.80 1.07 724

Non-Whites

3.36 1.06 286

Total 2.96 1.10 1010

29

ClassroomEnvironment

High SES Whites 3.72 .87 304Non-

Whites

3.36 .95 43

Total 3.68 .88 347Middle SES Whites 3.69 .90 285

Non-Whites

3.68 .66 14

Total 3.69 .88 299Low SES Whites 4.32 .82 135

Non-Whites

4.64 .52 229

Total 4.52 .66 364Total Whites 3.82 .90 724

Non-Whites

4.40 .77 286

Total 3.98 .90 1010Musical

Ability High SES Whites 3.71 .81 304

Non-Whites

3.42 .88 43

Total 3.67 .82 347Middle SES Whites 3.68 .84 285

Non-Whites

3.80 .66 14

Total 3.69 .83 299Low SES Whites 3.78 .82 135

Non-Whites

3.72 .82 229

Total 3.75 .82 364Total Whites 3.71 .82 724

Non-Whites

3.68 .83 286

30

Total 3.70 .82 1010

Table 2 (cont.)Descriptive Statistics for Socioeconomic Status and Ethnicity on the Five SubscalesMAOS Subscales Socioeconomi

cStatus

EthnicGroup

Mean StandardDeviatio

n

N

Affect for Music

High SES Whites 3.03 1.20 304Non-

Whites

2.63 1.29 43

Total 2.98 1.22 347Middle SES Whites 3.00 1.23 285

Non-Whites

3.05 1.11 14

Total 3.00 1.23 299Low SES Whites 3.19 1.23 135

Non-Whites

3.05 1.18 229

Total 3.10 1.20 364Total Whites 3.05 1.22 724

Non-Whites

2.99 1.20 286

Total 3.03 1.21 1010

The independent variables (IVs) for the two-way MANOVA

were socioeconomic status and ethnic group. The dependent

variables (DVs) for the two-way MANOVA were the five MOAS

subscales, effort, background, classroom environment,

31

musical ability, and affect for music. The main effects and

the interaction between the IVs, socioeconomic status and

ethnicity, are represented in Table 3. Pillai’s Trace was

substituted for Wilks’ Lambda because there was no

homogeneity of covariances (Wilcox, 2012), illustrated by

Box’s Test of Equality of Covariance, Box M = 367.06,

F = 4.67 df = 75, 17620, p < .001.

Table 3Main Effects of the Independent Variables and their Interaction

Variable Pillai’sTrace

F Significance

df Power

SES .19 20.68 < .001 10, 2002 1.00Ethnicity .00 .56 < .73 5, 1000 .21SES x Ethnicity

.03 2.77 < .01 10, 2002 .97

For socioeconomic status (see Table 3), Post-Hoc

analyses of variance (ANOVAs) revealed main effects,

significance differences, for three of the MAOS subscales,

effort, background and classroom environment.

The third research question investigated whether

ethnicity impacted the variables cited as most important. No

significant difference, no main effects, were found in the

Post-Hoc ANOVA for ethnicity (see Table 3).

32

There was a significant interaction between

socioeconomic status and ethnicity variables. According to

Wilcox (2012) significant interactions between independent

variables are highly important. Two MAOS subscales varied as

a function of both socioeconomic status and ethnicity,

effort F = 5.32, df = 2, 1004, p < .01, Power = .84, and

classroom environment F = 9.41, df = 2, 1004, p < .001,

Power = .98. The estimated marginal means for these two

subscales are illustrated below in Table 4.

Table 4Estimated Marginal Means

MAOSSubscale

s

Socioeconomic

Status

EthnicGroup

Mean StandardError

95% Confidenc

eInterval

Effort High SES Whites 4.05 .04 3.98-4.12Non-

Whites

3.78 .09 3.60-3.97

Middle SES Whites 4.02 .04 3.95-4.09Non-

Whites

4.07 .17 3.75-4.39

Low SES Whites 4.33 .05 4.23-4.43Non-

Whites

4.45 .04 4.37-4.53

Classroom High SES Whites 3.72 .05 3.63-3.82

33

Environment Non-Whites

3.36 .12 3.12-3.60

Middle SES Whites 3.69 .05 3.60-3.78Non-

Whites

3.68 .22 3.26-4.11

Low SES Whites 4.32 .07 4.18-4.45Non-

Whites

4.64 .05 4.53-4.74

Results indicated that this interaction was highly

complex (see Table 4). For effort, high socioeconomic status

Non-White subjects had a lower mean than high socioeconomic

status White subjects; whereas low or middle socioeconomic

status Non-White students placed more importance on effort

than White learners.

For classroom environment (see Table 4), Non-White

means differ variably from White means depending on

socioeconomic status. Lower socioeconomic status Non-White

subjects cited classroom environment as more important than

lower socioeconomic status White subjects. Middle

socioeconomic status Non-White students placed a relatively

equal importance on classroom environment than White

students. Lastly, high socioeconomic status Non-White

34

learners cited classroom environment as less important than

White learners.

According to Santrock (2006) achievement motivation

levels among various ethnicities differ widely. However,

when ethnicity and socioeconomic status are investigated in

the same study, socioeconomic status tends to be a better

predictor of achievement (Santrock, 2006). This possibly

explains the results of the Post-Hoc ANOVAs. Significant

differences were found for the socioeconomic status

independent variable, and not for the ethnicity variable.

Limitations were discovered in the output while

producing the two-way MANOVA. Box’s Test of Equality of

Covariance Matrices revealed no homogeneity of covariances,

and Levene’s for Equality of Variances showed that the means

of the variances between groups were unequal. According to

Wilcox (2012), the two-way MANOVA is a robust test, and

results can be interpreted. Larger sample sizes of Non-White

subjects in future research may diminish these limitations.

V. Conclusion

35

The first research question examined which subscale

variables from Asmus’ (1986b) Music Attribution Orientation

Scale were most attributed to success or failure in music.

The results of this investigation indicated that second

grade music students believed that effort and classroom

environment were the most important variables for success or

failure in music with mean scores of 4.16 and 3.98,

respectively.

The second research question investigated whether

socioeconomic status impacted the variables cited as most

important. Socioeconomic status had a significant impact for

the effort, background, and classroom environment subscales.

The third research question investigated whether

ethnicity impacted the variables cited as most important.

Ethnicity did not significantly impact any of the MAOS

subscales. A significant interaction between socioeconomic

status and ethnicity was found. The levels of two MAOS

subscales, effort and classroom environment, varied as a

function of the socioeconomic status and ethnicity

variables.

36

In music education, teachers may consider encouraging

second grade students with effort attributions. With these

actions taken, students may be more likely to carry the

belief that if they work hard at a musical task, they can

achieve more in music. In addition, the educator must

provide a positive classroom environment. When the educator

builds a positive rapport with the students, and supports

positive relationships among their pupils, second graders

may feel like they can achieve in music at a higher level.

Sociocultural variables could also be considered when

music educators are trying to motivate their learners.

Different motivational techniques may benefit certain

populations of socioeconomic status or ethnicity more than

others. As results in the present investigation suggested,

the interaction between socioeconomic status ethnicity is

highly complex. In highly diverse populations, employing

many motivational techniques may benefit the greatest

percentage of students.

Limitations found in this study warrant further

research into this topic. More data should be collected on

37

Non-White populations for a more accurate, and in-depth

comparison. Further, a new scale could be developed for use

with younger populations. It is encouraged that, after the

development of a new scale, a more comprehensive examination

be done including second grade music students in comparison

to younger and older students.

38

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Appendix A

Music Attribution Orientation Scale(MAOS)

Directions: Thank you very much for completing thefollowing survey. Please follow the directions on

the tape very carefully, and do not begin thesurvey until instructed to do so. The purpose ofthis survey is to determine your attitudes towardvarious aspects of music and musical activities.Because the items determine only your attitudes,

there are no right or wrong answers.

Indicate how important you believe each cause is indetermining success and failure in music by

circling 1 through 5. Where,1 is not important at all to

5 which is extremely important.

For example, if you read, “Having long fingers,”and felt that it was not very important, you would

circle the number 2.

1          2          3          4          5

On the other hand, if you read the cause, "Being acareful worker," and felt that it was somewhat

important, you would circle the number 4.

1          2          3          4          5

Please indicate the heritage or ethnic backgroundyou identify with:

43

_____ American Indian or Alaska Native

_____ Asian

_____ Black or African American

_____ Hispanic or Latino

_____ Native Hawaiian or Other Pacific Islander

_____ White, Not Hispanic or Latino

44

45

46