Phillip M. Hash Calvin College Grand Rapids, Michigan pmh3@calvin.edu Development and Validation of a Music Self-Concept Inventory for College Students Phillip M. Hash Calvin College Grand Rapids, Michigan pmh3@calvin.edu

Purpose Develop a brief music self-concept inventory for college students Easy to score Reliable Tests 3-factor model Use My interest Develop a brief music self-concept inventory for college students easy to administer tests a three-factor model defined by Austin (1990) demonstrates acceptable internal reliability of α ≥ .80 Useful to researchers and educators who want to measure music self-concept among students

Definition Self-concept: “An individual’s relatively stable and organized perception and evaluation of themselves within socially important domains that are formed through experience with and interpretations of one’s environments.” (Marsh, Parker, & Craven, 2015, p. 116; also see Shavelson, Hubner, & Stanton, 1976) Term sometimes used interchangeably w/ self-esteem Self-concept is hierarchical. Individuals hold both global self-concept and more specific self-concepts about different areas in their lives. The hierarchy can progressively narrow from beliefs regarding academic and non-academic aspects into more discreet types of self-concepts such as those related to specific academic areas (e.g., language arts, math), social relationships (e.g., family, peers), or physical traits (e.g., height, complexion) (Pajares & Schunk, 2001).

Self-Concept Model (Shavelson, Hubner, & Stanton, 1976) Language Math

Self-Concept Model Including Artistic Domain Vispoel (1995)

Music Self-Concept (Vispoel, 1994)

Three- Factor Model of Music Self-Concept (Schmitt, SEMA, 1979; Austin, 1990) Support/ Recognition from Others Personal Interest/ Desire MUSIC SELF CONCEPT Model of Global Music Self Concept 3 factors: Influence of Others; Interest & Desire; Perceptions of Ability This model comes from a study by Schmidt (1979) who developed the Self-Esteem of Music Ability scale in a dissertation. This scale for adolescents 10-15 years old Contained 43 items Factor analysis indicated the subcales, which Austin (1990) further refined. Perception of Music Ability

Need for Measuring Music Self-Concept Self-Concept Can Influence Decisions to participate & persist Achievement & enjoyment (Marsh, Craven, Mclnerney, 2003) Reciprocal Effects Model (Marsh & Martin, 2011) Develop both Self-Concept & Achievement MSCI a tool to help ID instructional strategies ID populations who might benefit from curricular revision or intervention Relationship of self-concept & achievement Achievement and self-concept are causes and effects of each other (reciprocal effects model) Need to work towards both in education (Marsh & Martin, 2011) Self Concept influences participation persistence enjoyment Music self-concept can influence decisions to participate and persist affect music achievement and enjoyment Value of measuring music self-concept: Identify instructional strategies that prove effective for increasing this characteristic (e.g., Randels, 2010; Sanders, 2000) Identify students who might benefit from curricular revision (Gumm, 1990) various forms of intervention (e.g., Austin & Vispoel, 1998; Sichivitsa, 2004)

Instrument Development Examined Self-Esteem of Music Ability (SEMA) (Schmidt, 1979) Children/Adolescents age 10-15 Used recently by Draves (2008); Randels (2010); & Kruse (2012) 43 positively & negatively stated items Factor Analysis indicated 3 subscales Also VanderArk (n.d.) & Svengalis (1978) Created New Items Based on SEMA (reworded & stated positively) Some items original Examined Self-Esteem of Music Ability (SEMA) (Schmidt, 1979) Used recently by Draves (2008); Randels (2010); & Kruse (2012) 43 positively & negatively stated items Created new items Based on SEMA (reworded & stated positively) Some items original

Instrument Development Demographic Information 15 Statements/3 Equal Subscales (Others, Interest, Ability) Sent to 3 music education faculty (face validity) Conducted Pilot Test Revise Ability Subscale Proceeded to Main Study Demographic Information Gender Age/college year Music Experience in and out of school Fifteen statements in three equal subscales (Others, Interest, Ability) Five-point Likert Scale (1 = strongly disagree, 5 = strongly agree) Sent to three music education faculty (face validity) Conducted Pilot Test Indicated need to revise some statements in the ability subscale due to low reliability Proceeded to Main Study As a measure of construct validity, a subset of respondents (n = 55) also completed a modified version of the SEMA in order to determine the correlation between total and subscale scores on this instrument and the MSCI

Administration Small LA College in Midwest Completed by Intact Classes for Non Music Majors (N = 237) Administered by Researcher Scripted Instructions To measure construct validity, a subset (23%) also completed a modified version of the SEMA in order to determine the correlation between total and subscale scores on this instrument and the MSCI

Data Analysis – Reliability & Validity Internal reliability (α) Construct Validity (SEMA vs. MSCI) Criterion Validity (music participation & gender) Discriminant Validity (factor r) Factor Analysis Exploratory (eigenvalue = 1 criteria) Confirmatory (constrained to 3 factors) Principal Axix w/ Promax Rotation Descriptive Statistics Cronbach’s alpha (internal reliability of scale and subscales) Correlation (factors, MSCI vs. SEMA) Factor Analysis Principal Axis w/ Kaiser Normalization Promax rotation (correlated items) Exploratory (eigenvalue = 1 criteria) Confirmatory (constrained to 3 factors)

Participants (N = 237) Male = 41%; Female = 58%; Unspecified = 1% 18 to 48 years of age (M = 19.87, SD = 2.77) Freshman (n = 27%), sophomore (n = 30%), junior (n = 25%), and senior (n = 19%) classes White (n = 73%) and non-White (n = 27%) Determined by photographs & instructor knowledge of students In-school music participation: 0 - 15 (M = 5.86, SD = 3.82) years Out of school music participation: 0 - 17 (M = 6.10, SD = 4.66) Combined participation: 0 - 30 (M = 12.06, SD = 7.24) years Male = 40.9%; Female = 57.8%; Unspecified = 1.3% 18 to 48 years of age (M = 19.87, SD = 2.77) Freshman (n = 26.6%), sophomore (n = 29.5%), junior (n = 24.9%), and senior (n = 19.4%) classes White (n = 73.4%) and non-White (n = 26.6%) Determined by photographs & instructor knowledge of students In-school music participation: 0 - 15 (M = 5.86, SD = 3.82) years Elective Ensembles & classes Out of school music participation: 0 - 17 (M = 6.10, SD = 4.66) Community or church groups and private lessons Combined participation: 0 - 30 (M = 12.06, SD = 7.24) years

Initial Draft - Results Reliability - Total Scale: α = .95; Subscales: α = .84 - .92. Bartlett’s test (χ2 = 2552.22, p < .001) = correlations appropriate for factor analysis KMO measure (.94) = adequate sample size Subject-to-variable ratio = 15.8:1. MAIN STUDY

Initial Draft - Factor Analysis Exploratory (59.5% variance) 2 factor solution (a) perception of abilities with influence from others and (b) personal interest or desire Confirmatory (63.1% variance) 8.57 (others), 1.18 (interest), 0.84 (abilities) Items intended to constitute each factor loaded highest under their respective columns. “I am a capable singer or instrumentalist” & “I can be creative with music” were deleted due to cross-loadings.

Final Version 13 items Reliability - Total scale: α = .94; Subscales α = .83 - .92 Factor analysis explained 63.6% of the variance All but one of the rotated factor loadings exceeded .50 Eigenvalues = 7.37 (others), 1.17 (interest), and 0.84 (abilities) Subscale scores (r = .65 - .72) Subscales vs. total scale (r = .84 - .94) 13 items Reliability - Total scale: α = .94; Subscales α = .92 - .83 Factor analysis explained 63.6% of the variance Influence of others (54.1%), interest (5.7%), and ability (3.7%) All but one of the rotated factor loadings exceeded .50 Eigenvalues = 7.37 (others), 1.17 (interest), and 0.84 (abilities) Subscale scores moderately correlated with each other (r = .65 - .72) and highly correlated to the total scale (r = .84 - .94) Interfactor correlations (r = .71 - .75) met the ≤ .85 cutoff that generally serves as the criterion for discriminant validity in applied research (Brown, 2015) High correlation w/ SEMA: total .94; subscales .80 - .85

Validity MSCI & SEMA: total (r = .94; subscales r = .80 - .85) – Construct Interfactor correlations (r = .71 - .75) – Discriminant In School (r = .51), Out-of- School (r = .58), & Total (r = .64) Participation - Criterion MSCI scores males vs. females non-significant (ANOVA) ANCOVA controlling for total participation found males significantly outscored females Supported by some literature (e.g. Simpkins, Vest, & Becnel, 2010)

Pattern Matrix for Principal Factor Analysis with Promax Rotation of the MSCI (final version)   Factors Item I Others II Interest III Abilities My family encouraged me to participate in music. .95 I have received praise or recognition for my musical abilities. .92 Teachers have told me I have musical potential. .85 My friends think I have musical talent. .60 .32 Other people like to make music with me. .52 .39 I like to sing or play music for my own enjoyment. Music is an important part of my life. .74 I want to improve my musical skills. .71 I enjoy singing or playing music in a group. .62 I like to sing or play music for other people. .56 I can hear subtle differences or changes in musical sounds. .84 I have a good sense of rhythm. .76 Learning new musical skills would be easy for me. .45

Conclusions The MSCI effectively measures music self-concept as described by 3- factor model Use the MSCI to (a) assess change or development in music self- concept, (b) identify differences in various aspects of music self- concept, (c) compare music self-concept among different populations, or (d) examine relationships between music self-concept and other variables Use MSCI scores to (a) assess students’ attitudes towards their musical potential and accomplishment and (b) identify students who might require extra support

Conclusions The MSCI might be useful for students below the college level. Future studies should test the MSCI among people of varying ages and backgrounds, and examine additional variables, models, and theories that might explain this construct. The MSCI might be useful for students below the college level. The structure of music self-concept likely does not change between junior high school and college (Vispoel, 2003). Flesch-Kincaid Reading Ease score of 67.3. Average grade level reading score of 7.0 (Readability-Score.com). MSCI might be effective with students as young as middle school. Future studies should test the MSCI among people of varying ages and backgrounds, and examine additional variables, models, and theories that might explain this construct (e.g., Schnare, MacIntyre, & Doucett, 2012).