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
Draft of Three Year Schedule
Academic
Year
Fall
Winter
Spring
2006-07
EDLD 610 Multiple Regression
SPSY 620 Multivariate
SPSY 618 Stats I
EDLD 610 Structural Equation
Modeling II
SPSY 619 Stats II
EDLD 610 Hierarchical Linear Models I
2007-08
(502 Measurement & Assessment –
old SPSY 617)
(504 Research Design)
(510 Intro Stats-old SPSY 618) (RG)
SPSY 620 Multivariate (JS)
680 Large Scale Databases (KZ)
IRT I (PY)
602 Applied Stat. Design & Analysis
(RG)
610 Survey Design and Analysis (JS)
IRT II (PY)
(510 Intro Stats)
606 Multivariate
641 SEM I
602 Applied Stat. Design & Analysis
642 SEM II
660 Advanced Research Design
(510 Intro Stats)
606 Multivariate
631 HLM I
602 Applied Stat. Design & Analysis
632 HLM II
EDLD 610 Multiple Regression
(JS)
632 HLM II
2008-09
(502 Measurement & Assessment)
(504 Research Design)
604 Multiple Regression
670 Categorical
2009-10
(502 Measurement & Assessment)
(504 Research Design)
604 Multiple Regression
Upcoming Activities
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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!)