COE Quantitative Methods Curriculum Committee Scott Baker David Chard (ex-Officio) Roland Good Ben McWhirter Maya O’Neil (graduate student member) Kathleen Scalise Joe Stevens (Chair) Deanne Unruh Paul Yovanoff http://www.uoregon.edu/~stevensj/QMCC.ppt
Committee Work • Review and refine new doctoral curriculum in quantitative methods • Make recommendations on implementation • Foster communication on changes • Prepare curricular change forms • Explore certificate in methods • Explore MA in EDLD with an emphasis on educational research methods
New Course Sequence The doctoral sequence presumes three MA level courses (EDUC 502, 504 and 510) as prerequisites. Provisions will be made to allow Ph.D. students to test out of either of these courses or submit transcripts and syllabi to demonstrate successful completion of a comparable course. EDUC 502 Educational and Psychological Measurement and Assessment EDUC 504 Research Design in Education EDUC 510 Introduction to Educational Statistics
EDUC 515 Use of Statistical Software in Educational Research (MA or PhD; 1 unit course) This 1 unit course provides an introduction to the SPSS statistical package including use of the data editor, syntax editor, and output viewer; basic data transformations including “compute” and “if” statements; recoding of variables; data management procedures including select cases, sorting, merging, and aggregating; basic use of graphing procedures. Prerequisite: None.
DOCTORAL COURSES: EDUC 602 Applied Statistical Design and Analysis(formerly SPSY 619) Includes factorial analysis of variance (ANOVA), planned comparisons, post hoc tests, trend analysis, effect size and strength of association measures, repeated measures designs. Consideration of alternative strategies in research design and comparison of research designs. Emphasis on solving applied problems using SPSS for Windows. Prerequisite: EDUC 510 EDUC 604 Multiple Regression in Educational Research Includes bivariate regression, multiple regression with continuous and categorical independent variables, regression diagnostics, interactions, orthogonal and nonorthogonal designs, selected post hoc analyses, logistic regression. Computer analysis using SPSS for Windows, conceptual understanding, and applications to educational research are stressed. Prerequisite: EDUC 602 EDUC 606 Applied Multivariate Statistics (formerly SPSY 620) Advanced statistical techniques including covariance analyses (ANCOVA, MANCOVA), discriminant function analysis (DFA), multivariate analysis of variance (MANOVA), principal components analysis (PCA), exploratory factor analysis (EFA). Emphasis on use and interpretation of analysis using SPSS for Windows. Prerequisite: EDUC 604
EDUC 610 Survey and Questionnaire Design and Analysis (MA or Ph.D. level) Covers survey research from item writing and survey development to sampling, administration, analysis and reporting. Emphasizes applications and interpretations in educational and social science research and use and interpretation of statistical software for survey research. Prerequisite: EDUC 502 EDUC 614 and 615 Program Evaluation I & II These courses will provide theoretical and conceptual foundations along with techniques for evaluating social programs, specifically for education and human services. Methods to conduct needs assessments and process, outcome, and impact evaluations will be included in this applied sequence. Activities will include designing, implementing, and reporting on a social program evaluation. During the first term students will design an evaluation with a specified client and conduct the evaluation during the second term. Prerequisite: EDUC 501 & 502 or equivalent EDUC 616 Advanced Program Evaluation The course focuses on the analysis of evaluation data. Topics include issues that arise in program evaluation contexts including alternative research designs (e.g., regression discontinuity), matching, use of propensity scoring, methods for exerting experimental and statistical control in applied settings, time series designs, and the modeling of treatment fidelity data both as a predictor and outcome. Prerequisite: EDUC 604 and 615
EDUC 618 Multiple/Mixed Method Inquiry Theory and practice of mixed and multiple inquiry methodologies in applied research, assessment and evaluation. Includes history and philosophies of mixed inquiry, a framework for mixed method design and analysis, analytic strategies, selected examples and challenges. Students should have basic familiarity with such topics as experimental or survey research (quantitative) and constructivist or interpretivist (qualitative) social science. Prerequisites: EDUC 602 and EDLD 660 or equivalents. EDUC 620 Exploratory Factor Analysis Principal components analysis, theory and method of common factor analysis, extraction, rotation, and estimation methods. Applications to instrument development and validation of measures. Use and interpretation of statistical software. Prerequisites: EDUC 604 EDUC 631 Multilevel Modeling I Introduction to multilevel modeling and hierarchical data structures, random and fixed effects, intercepts and slopes as outcomes models, estimation, centering, emphasis on two level models, use and interpretation of statistical software. Prerequisites: EDUC 604
EDUC 632 Multilevel Modeling II Advanced topics in multilevel modeling and hierarchical data structures including three level models with random and fixed effects, longitudinal models, multilevel models for binary and categorical outcomes, applications in IRT and meta-analysis. Prerequisites: EDUC 631 EDUC 641 Structural Equation Modeling I Theory, application, interpretation of Structural Equation Modeling (SEM) techniques. Includes covariance structures, path diagrams, path analysis, model identification, estimation, and testing. Emphasis in the first quarter is on measurement models and confirmatory factor analysis as well as the use of invariance testing of measurement models. Prerequisite: EDUC 604 EDUC 642 Structural Equation Modeling II Theory, application, interpretation of Structural Equation Modeling (SEM) techniques. Includes covariance structures, path diagrams, path analysis, model identification, estimation, and testing. Emphasis in the second quarter is on structural and latent variable models, including cross-validation, mean structures, comparing groups and models, latent growth curve analyses. Prerequisite: EDUC 641
EDUC 650 Advanced Seminar in Educational Research Methods Seminar introduces advanced students to current research designs and controversies, statistical analysis techniques, and computer applications. Considers special issues in the use and application of educational statistics and research design in a group discussion/seminar format (e.g., nonparametric statistics, meta-analysis, “evidence-based” research design). Topics will vary by quarter; may be repeated for credit. Prerequisite: EDUC 602 EDUC 660 Advanced Research Design in Education In depth consideration of current issues in quantitative research methods and research designs. Intended to provide a deeper understanding of educational research with an emphasis on principles of research design and their use in applied research. Topics covered include internal, external and construct validity; experimental and nonexperimental designs; longitudinal designs; sampling methods; control of confounding; multilevel designs; standards and ethics. Prerequisite: EDUC 602 EDUC 670 Analysis of Discrete and Categorical Data Advanced methods for analysis of discrete data. Topics covered include log-linear, logit, probit, latent class and mixture models, and other generalized linear models. Description and statistical inference for contingency tables, dichotomous and polytomous measures; log-linear and other generalized linear models for two or more dimensions; testing goodness of fit, estimation of model parameters, hierarchical model fitting, diagnostics. Prerequisite: EDUC 604
EDUC 680 Analysis of Large Scale Databases The course is designed to introduce students to secondary data analysis and the use of data from national and other databases. Existing data sources will be explored. Students will receive experience working with an existing data base especially those available from the National Center for Education Statistics (NCES). Topics covered will include complex sample designs, weighting, design effects, imputation, multilevel data structures. Students will conduct a research project using an existing data base. Prerequisite: EDUC 604 EDUC 690 Advanced Practicum in Quantitative Methods This course is designed to provide structured consultation and applications for advanced graduate students. Prerequisite: EDUC 604
MEASUREMENT AND ASSESSMENT COURSES: Validity Theory (formerly EDLD642) (4 units) Focus on validity theory as defined in the Joint Test Standards. Discussion of validity situated in a historical context to provide students with a better understanding of the social framework of decision-making, use, and interpretations of assessment results. Instrument Development (New Course) (4 units) Experience and practice in instrument development across a range of instrument types (achievement, aptitude, psychological, personality, etc.) and formats (selected and constructed response, performance assessment, surveys and questionnaires, observation protocols, etc.). Students will gain experience in considering measurement constructs, developing items/tasks for various formats, defining outcome spaces and use of various measurement models to interpret evidence.
Advanced Measurement and Assessment in Education (formerly EDLD642) (4 units) Current topics and issues in measurement, assessment, and testing including scaling, standard setting, item and scale analysis, bias and fairness, DIF, equating, norming, using assessments for decisions and policymaking. Concepts situated in both classical and item response theory. Test development topics will include construct representation, alignment to curriculum and instruction, and domain and skill sampling. Item Response Modeling I and II (formerly EDLD 661 and 662) (4 units) Study of Item Response Theory (IRT) in which participants will be exposed to popular item response models, applications, and relevant resources, including journals, software, and websites. In addition to the text and readings, participants will use WINSTEPS software for Rasch modeling.
EDLD RESEARCH FOUNDATIONS SEQUENCE FOR THE D.Ed. DEGREE 610 Foundations of Educational Research The three quarter sequence prepares students to complete their dissertation research. The competencies emphasized in the three quarter research sequence pivot around the central theme of 'evidence-based' inquiry and practice. Throughout, research perspective and communication skills are emphasized. Foundations of Educational Research I - The first quarter emphasizes the design of inquiry including variables and measurement in the context of explicit investigative arguments; internal and external validity; relative strengths and weaknesses of various designs; analysis of examples with respect to 'validity'. Foundations of Educational Research II - The second quarter is an in-depth study of operational educational research designs, methods and conclusions drawn from a data collection process. Data are provided with the requirement that summaries and graphic displays be used for appropriate presentation. Communication skills (written and oral) are emphasized. Foundations of Educational Research III - The final, third quarter in the sequence is the culmination of conceptual knowledge and skill acquisition; requires application of research principles, with a focus on the dissertation proposal preparation; small-scale exercises in design and implementation; emphasis on presentation skills (written and oral) including a 'poster' describing a design, results and conclusions.
Statistical Software • In concert with decision of area heads, committee debated software. Consensus decision to adopt SPSS for Windows • Graduate Pack, about $200 • Working on site licensing • SPSS used throughout the sequence; specialized software in some advanced courses
Upcoming Activities • Brochures for students and faculty advisors • Visits with departments/programs • SPSS workshops • Colloquia on Methods • Power & Effect Size? • Multilevel Models, HLM? • Student recruitment, scheduling & coordination • UO committee on research support (thanks to those who have sent in information!)