College
of Education Quantitative Research Methods Course Descriptions
This is the new course sequence in quantitative research methods in the
Sample programs of study are provided in a separate document. We also anticipate the development of a university certificate program in quantitative research methods. Of course, individual courses listed below can also be adopted by individual degree programs to fulfill requirements for particular degrees or as elective coursework.
There is also a three quarter educational research methods sequence in EDLD for the D.Ed. degree that is oriented toward consumers of research who are practitioners in their professional lives and who do not have a goal of producing research. The D.Ed. sequence is available to others in the college with a similar orientation and is listed at the end of this document. However, the D.Ed. sequence does not fulfill any requirements for COE Ph.D. degrees.
The current plan is to use a college, EDUC course prefix for the fundamental courses in the sequence. More specialized courses may reside in particular departments and retain a departmental prefix. Course numbers in this document are listed in order and may change in the future. Other curriculum development in qualitative and single subject methods is also in development by other faculty groups in the college.
MASTER’S LEVEL COURSES:
EDUC 502 Educational and Psychological Measurement and Assessment (MA level)
Classical and modern approaches to measurement and assessment as applied in Education and Psychology. Survey of the major types of assessments in common use including achievement tests, aptitude tests, alternative assessment, attitude scaling, and personality assessment. Topics and issues in measurement and assessment including measurement and scaling, reliability and validity, test evaluation, ethics and standards, test development and analysis, and test fairness.
EDUC 504 Quantitative Research Design in Education (MA level)
Overview of quantitative and qualitative research methods for research producers. Provides students with skills for designing educational research, including identifying a problem, reviewing literature, formulating hypotheses, designing studies, selecting participants, selecting or constructing measures, making valid inferences, writing reports.
EDUC 510 Introduction to Educational Statistics (MA level)
Foundations of statistical methods for research producers. Covers sampling methods, descriptive statistics, standard scores, distributions, estimation, statistical significance testing, t-tests, correlation, chi-square, power and effect size using SPSS for Windows and computation. Prerequisite: EDUC 502 and 504
EDUC 515 Use of Statistical Software in Educational Research (MA or PhD)
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 FOR COE Ph.D. STUDENTS:
EDUC 602 Applied Statistical Design and Analysis
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 510
EDUC 606 Applied Multivariate Statistics
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 612 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 602 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
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:
These courses assume EDUC 503 at the MA level as a prerequisite. Other college courses in measurement and assessment may need to be considered and added here.
Validity Theory (formerly EDLD642)
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)
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)
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)
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 I, II, and III
The three quarter sequence is design to prepare students for candidacy to complete their dissertation research experience and receive the UO College of Education Educational Leadership Doctor of Education degree. 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.
The first quarter cultivates competencies related to the design of inquiry. Important research concepts include variables and measurement in the context of explicit investigative arguments. Perspectives on classic ideas of internal and external validity are developed through discussion about the relative strengths and weaknesses of various investigative designs. A rigorous analysis of examples with respect to 'validity' occurs throughout the first quarter.
The second quarter is an in-depth study of operational educational research designs, methods and conclusions drawn from a data collection process. All quarter one concepts are reinforced and situated in very specific procedures. Data are provided with the requirement that summaries and graphic displays be used for appropriate presentation. Communication skills (written and oral) are emphasized.
The final, third quarter in this sequence is the culmination of conceptual knowledge and skill acquisition. Quarter three requires application of research principles, with a distinct focus on the D.Ed. dissertation proposal preparation. Small-scale exercises in design and implementation are routinely required. The exercises cultivate presentation skills (written and oral) appropriate for different audiences (conference, staff, etc.), including a 'poster' describing a design, results and conclusions. (Depending on the size of this section, the projects may necessarily be conducted in student pairs.).
SINGLE
SUBJECT RESEARCH COURSES
SPED 607 Single Subject Research Methods I
This is the first course in the single subject research methods sequence. It focuses on basic single subject design strategies and general procedures as well as on issues related to conducting and analyzing single subject research in applied settings. The course covers general methodological information as well as specific details about single subject designs. Procedures for the collection and visual analysis of data are covered. Prerequisite: EDUC 510
SPED 608 Single Subject Research Methods II
This advanced course in single subject research methods is the second course of a two-course sequence. It is expected that students in this course will be familiar with the various types of single subject designs that are commonly used in applied research. This course will provide a critical evaluation of single-subject and group-analysis research designs. It also provides an elaboration on critical topics in single subject methodology and addresses issues faced by single subject researchers in conducting applied research in typical school, home, and community settings. Prerequisite: SPED 607
SPED 654 Advanced Applied Behavior Analysis
This course is a doctoral level seminar designed to provide skills,
practice, and knowledge in advanced methods and theory of Applied Behavior
Analysis (ABA). Emphasis will be placed on the theory, principles, procedures
and science of
In addition, students adopting an emphasis in single subject research methods will take at least one advanced quantitative course like EDUC 631 Multilevel Modeling I.