1. Review and Writers’ Workshop Class 7 Meetings at 11:30am Cathrine, Jeff, Alisha

2. For Tomorrow Complete chapter 3 Work on revising lit reviews (due Thursday) Read one article from the Journal of Historical Research in Music Education (on JSTOR) Find one interesting to you. Must be a full length article and not a book review. Be prepared to summarize for the class

3. Method Section https://owl.english.purdue.edu/owl/resource/670/04/ https://owl.english.purdue.edu/owl/resource/670/04/ Participants Data Collection/Research Instrument Data Analysis/Statistical Procedures Presentation/organization of the data See APA manual Examples online

4. Correlation What does correlation do? How is it different from Inferential Stats? What are 2 types of correlation? Describe Correlation in relation to direction & strength. Use data below to illustrate. What can correlation do and not do? What is r? what is r s ? What is r 2 Discuss significance in relation to correlation. What is Cronbach’s alpha? When would you use it? When would you not use it? 50 75 9 40 62 14 35 53 20 24 35 45 15 21 58

5. Statistical Assumptions The mathematical equations used to determine various correlation coefficients carry with them certain assumptions about the nature of the data used… Level of data (types of correlation for different levels) Normal curve (Pearson, if not-Spearman) Linearity (relationships move parallel or inverse) Young students initially have a low level of performance anxiety, but it rises with each performance as they realize the pressure and potential rewards that come with performance. However, once they have several performances under their belts, the anxiety subsides. (non linear relationship of # of performances & anxiety scores) Presence of outliers (all) Homoscedascity – relationship consistent throughout Performance anxiety levels off after several performances and remains static (relationship lacks Homoscedascity) Subjects have only one score for each variable Minimum sample size needed for significance

6. Other Stats

7. Chi-Squared http://vassarstats.net/ http://www.quantpsy.org/chisq/chisq.htm http://vassarstats.net/ http://www.quantpsy.org/chisq/chisq.htm Measure statistical significance b/w frequency counts (nominal/categorical data) Test for independence/association: Compare 2 or more proportions Example: Proportion of females to males in choirs at 2 district HSs. Goodness of Fit: compare w/ you have with what is expected Example: Proportions of females to males in choir compared to school population MalesFemales School A Choir 25 75 School B Choir 45 90 MalesFemales HS Choir 25 75 HS Population/exp. 548/47 625/53

8. Effect Size (Cohen’s d) http://www.uccs.edu/~lbecker/ http://www.uccs.edu/~lbecker/ [Mean of Experimental group – Mean of Control group/average SD] The percentile standing of the average experimental participant (at 50 th percentile) if they were ranked in the experimental group. where someone ranked in the 50 th percentile in the experimental group would be ranked in the control group Effect sizes can also be interpreted in terms of the percent of nonoverlap of the treated group's scores with those of the untreated group. Use table to find where someone ranked in the 50 th percentile in the experimental group would be in the control group Good for showing practical significance When test in non-significant When both groups got significantly better (really effective vs. really really effective! Calculate effect size: Pretest: M=10.8; SD= 5.7 Posttest: M=24.6; SD=4.3 Calculate effect size for difference b/w composite scores of band & non- band students for 2007, 2008, 2009 (each choose 1)

9. Effect Size (d) Interpretation

10. Writer’s Workshop Email your lit review to your partner Read each other’s lit review and give feedback, ask questions, etc. Identify typos, format issues, and text that is unclear. Examine each other survey/test Ask me questions

11. Development and Validation of a Music Self -Concept Inventory for College Students

12. Abstract The purpose of this study was to develop a music self-concept inventory (MSCI) for college students that is easy to administer and reflects the global nature of this construct. Students (N = 237) at a private college in the Midwest United States completed the initial survey, which contained 15 items rated on a five- point Likert scale. Three subscales determined by previous research included (a) support or recognition from others, (b) personal interest or desire, and (c) self- perception of music ability. Factor analysis indicated that two items did not fit the model and, therefore, were deleted. The final version of the MSCI contains 13 items and demonstrates strong internal consistency for the total scale (α =.94) and subscales (α =.83 -.92). A second factor analysis supported the model and explained 63.6% of the variance. Validity was demonstrated through correlation (r =.94) between the MSCI and another measure of music self-perception, MSCI scores and years of participation in music activities (r =.64), and interfactor correlations (r =.71 -.75) indicating three distinct factors. This instrument will be useful to researchers examining music self-concept and to college instructors who want to measure this construct among their students.

14. Literature Terms: Self-concept (Am I?), self-esteem (+/- ?), self-efficacy (can I?) Previous measures Schmitt (1979) Ability Influence of Others Interest Svengalis (1978) Vispoel (1993, 1994) Self-Concept is Hierarchical (global vs. specific) SC can influence motivation, self-regulation, perseverance, participation, and probably achievement

15. Purpose & Need The purpose of this study was to develop a brief music self-concept inventory for college students that is easy to administer, tests the three-factor model defined by Austin (1990), and demonstrates acceptable internal reliability of α ≥.80 (e.g., Carmines and Zeller, 1979; Krippendorff, 2004). Such an instrument will be useful to researchers or college professors who want to measure music self-concept among their students.

16. Method The initial draft of the Music Self Concept Inventory (MSCI) consisted of 15 statements divided into three equal subscales related to (a) support or recognition from others, (b) personal interest or desire, and (c) perception of music ability (Austin, 1990). 2 pilot studies (N = 20) Main Study (N = 237) Also took SEMA (Schmitt, 1979) n = 55 Factor Analysis to confirm efficacy of the three factor model

17. Factor Analysis Pattern Matrix for Principal Factor Analysis with Promax Rotation of the MSCI (final version)