Instructor Information: Dr. Peter Miksza Office Hours: By appointment Simon 145H;

Transcription

1 1 Indiana University Jacobs School of Music, Music Education Advanced Quantitative Research in Music Education E Spring 2016 M, W: 2:30 to 4:00, Simon Library 373 (computer lab) Instructor Information: Dr. Peter Miksza Office Hours: By appointment Simon 145H; Course Description: This course is an exploration of principles and methods of quantitative research in music education. The first component of the course deals with a review and extension of fundamental considerations when conducting quantitative research including the nature of scientific inquiry and general guidelines for descriptive, correlational, and experimental research designs. The second component of the course deals with the introduction and application of intermediate and advanced statistical analysis methods necessary for more complex research designs: (a) extensions of ANOVA, (b) regression approaches, (c) factor analysis, and (d) structural equation modeling. Students will be challenged to critique existing research, pose hypothetical designs, and analyze and create reports with actual data sets. Students will also complete an original empirical study, preferably as a pilot work leading to their dissertation research. Required Texts Huck, S. W. (2013). Reading statistics and research (6 th ed.). New York, NY: Pearson. Gall, M. D., Gall, J. P., & Borg, W. R. (2007). Educational research: An introduction. New York, NY: Pearson. Leech, N. L., Barrett, K. C., & Morgan, G. A. (2013). IBM SPSS for intermediate statistics (5 th ed.). New York, NY: Routledge Nicol, A. A. M., & Pexman, P. M. (2011). Presenting your findings: A practical guide for creating tables. Washington, DC: American Psychological Association. Nicol, A. A. M., & Pexman, P. M. (2011). Displaying your findings: A practical guide for creating figures, posters, and presentations. Washington, DC: American Psychological Association. APA manual current edition Additional pdf readings and websites will be posted on Canvas Recommended Foundational Statistics Text Agresti, A., & Finlay, B. (2008). Statistical methods for the social sciences (4 th ed.). New York, NY: Pearson. Objectives: Upon completing this course students will be able to 1. Discuss basic notions emblematic of the scientific method and scientific work: a. Incremental scientific progress

2 2 b. Probabilistic thinking c. The roles of descriptive, correlational, and experimental methods d. Theory-driven hypotheses 2. Discuss major considerations for descriptive research designs and critique existing research 3. Discuss major considerations for correlational research designs and critique existing research 4. Discuss major considerations for experimental designs and critique existing research 5. Review the following statistical topics: a. Levels of data/measurement scales b. Basic indices of central tendency and dispersion c. Correlation and covariance d. Descriptive vs. inferential statistics e. Inference: null hypothesis significance testing, statistical significance, and confidence intervals i. t-tests ii. One-way ANOVA f. Parametric vs. Non-parametric inferential analyses g. Internal/external validity in experimental design vs. measurement 6. Run analyses, create tables, and write interpretations of findings when given data sets suited to the following procedures (SPSS) a. Mixed Design ANOVA, Factorial ANOVA, ANCOVA, MANOVA b. Multiple linear regression, logistic regression c. Exploratory factor analysis 7. Describe and critique research incorporating the following advanced statistical techniques: a. Multi-level modeling b. Confirmatory factor analysis c. Structural equation modeling 8. Apply the design concepts analytical tools discussed in the course to their own research interests and methodological design. The point breakdown of the course grade is as follows: Weekly Homework 280 Personal Project 125 TOTAL 405 Grading (in percentage): A B C D F Below 60 A B C D A B C D Assignments in addition to content, writing quality is an important criterion for each assignment: 1. Homework: Work will be assigned each week as practice for the methodological principles and analytical approaches discussed and demonstrated in class. This could include some or all of the following types of tasks: analyzing existing studies, proposing hypothetical designs, analyzing data, interpreting data, creating figures and tables. These assignments will be due on the corresponding Friday each week they are given.

3 3 2. Personal Project: Students will complete an original empirical study and produce a manuscript suitable for publication. Manuscript must conform to APA style. IU POLICY Accommodations for Religious Holidays: Please note the dates recognized by IU at ( Forms ). A student accommodation request form is available at this site. Please fill one out and bring it to class should the need arise. Academic Misconduct: The definition of academic misconduct and the procedures to be followed at IU in the case that a problem should occur can be found at See both the Code document itself and the IU Bloomington Procedures. Disabilities Students requesting accommodations for various types of disabilities are referred to the Office of Disability Services for Students (Franklin Hall 006, ). Adjustments in course requirements cannot be made until a written evaluation from this office is received. Please see:

4 4 Advanced Quantitative Research in Music Education Course Schedule - Miksza Date Topic Sub-Topics and Readings Science 1/11 Characteristics of science Miksza & Elpus, Characteristics of science (pdf) Miksza & Johnson, Theoretical frameworks in the JRME (pdf) 1/13 Theory-driven research Shaddish, Cook, & Campbell, Critique of science EXCERPT (pdf) Murnane & Willett, Theory in educational research (pdf) Platt, Strong inference (pdf) Description 1/20 Descriptive research design and analysis Miksza & Elpus, Descriptive research (pdf) Miksza & Elpus, Descriptive analysis (pdf) Borg, Borg, & Gall, Chapter 8 Borg, Borg, & Gall, Chapter 9 Huck, Chapter 2 Correlation 1/25 Correlational research design and analysis Miksza & Elpus, Correlational design and analysis (pdf) Borg, Borg, & Gall, Chapter 11 Huck, Chapter 3 1/27 Correlational research design and analysis Miksza, Relationships among impulsiveness, locus of control, sex, and music practice (pdf) Statistical inference, effect size, power 2/1 Statistical inference Miksza & Elpus, Inferential analysis (pdf) Huck, Chapter 8 2/3 Parametric vs. Non-parametric inference/transition to causal inference Siegel & Castellan, Non-parametric decision tree (pdf) Shaddish, Cook, & Campbell, Statistical conclusion validity and internal validity (pdf) Shaddish, Cook, & Campbell, Construct validity and external validity (pdf) Causal inference 2/8 Experimental research design and analysis Miksza & Elpus, Causation (pdf) Borg, Borg, & Gall, Chapter 12 Costa-Giomi, The effects of three years of piano instruction on children s cognitive development (pdf) 2/10 Experimental research design and analysis Borg, Borg, & Gall, Chapter 13 Analyses of complex designs: The ANOVA family 2/15 One-way ANOVA Huck, Chapter 11 Huck, Chapter 12 2/17 Repeated Measures ANOVA Leech, Barrett, & Morgan, Chapter 10 Huck, Chapter 14 2/22 Factorial/Mixed-design ANOVA Leech, Barrett, & Morgan, Chapter 9 Leech, Barrett, & Morgan, Chapter 10 Huck, Chapter 14 Henley, Effects of modeling and tempo patterns as practice techniques on the performance of high school

5 instrumentalists (pdf) 2/24 Factorial/Mixed-design ANOVA Silvey & Montemayor, Effects of internal and external focus of attention on novice s rehearsal evaluations (pdf) 2/29 ANCOVA Leech, Barrett, & Morgan, Chapter 9 Huck, Chapter 15 Flohr, Short-term instruction and young children s developmental aptitude (pdf) 3/2 MANOVA Leech, Barrett, & Morgan, Chapter 11 Huck, Chapter 19 Kinney, Selected demographic variables, school music participation, and achievement test scores of urban middle school students (pdf) 3/7 Catch Up Analyses of complex designs: Regression 3/9 Linear Regression Leech, Barrett, & Morgan, Chapter 6 Huck, Chapter 16 3/14 Linear Regression Parkes & Jones, Motivation constructs influencing undergraduate students choices to become classroom music teachers or music performers (pdf) 3/16 Moderation and Mediation Leech, Barrett, & Morgan, Chapter 7 3/28 NAfME Atlanta 3/30 Logistic Regression Leech, Barrett, & Morgan, Chapter 8 4/4 Logistic Regression Bergee & McWhirter, Selected influences on solo and small-ensemble festival ratings (pdf) 4/6 Multi-level Regression Leech, Barrett, & Morgan, Chapter 11 Miksza, Investigating relationships between participation in high school music ensembles and extramusical outcomes (pdf) 4/11 Catch Up Analyses of complex designs: Latent variable modeling 4/13 Exploratory Factor Analysis Miksza & Elpus, Exploratory and confirmatory factor analysis (pdf) Leech, Barrett, & Morgan, Chapter 4 Huck, Chapter 20 4/18 Exploratory/Confirmatory Factor Analysis Schmidt, Zdzinski, & Ballard, Motivation orientations, academic achievement, and career goals of undergraduate education majors (pdf) 4/20 Confirmatory Factor Analysis Miksza, An investigation of the 2 X 2 achievement goal framework in the context of instrumental music (pdf) 4/25 Structural Equation Modeling Miksza & Elpus, Structural equation modeling (pdf) Huck, Chapter 21 4/27 Structural Equation Modeling Harrison, Asmus, & Serpe, Effects of music aptitude, academic ability, music experience, and motivation on aural skills (pdf) FINAL PROJECT DUE MAY 4 th 5:00PM 5