Introductory Statistics
*While required, this course does not count toward the Ph.D. degree.

An introduction to descriptive and inferential statistics. In particular, students will learn descriptive statistics, graphical and numerical representations of information; measures of location, dispersion, position, and dependence; the normal distribution; and exploratory data analysis. Provides computer instruction on PC and Mac platforms and in the SPSS statistical package.

Interpretation and Evaluation of Research
*While required, this course does not count toward the Ph.D. degree.

This course will improve a students' understanding of the empirical research literature in education and psychology. It concentrates on developing the conceptual foundations of empirical research and the practical analytic skills needed by a competent reader and user of research articles. Topics address purpose statements, hypotheses, sampling techniques, sample sizes and power, instrument development, internal and external validity, and typical quantitative research designs. Exercises emphasize the critical evaluation of published research. 

Assessment and Test Construction 

This course addresses the major issues of educational assessment, with emphasis on the characteristics, administration, scoring, and interpretation of both formal and informal assessments, including but not limited to tests of achievement. All forms of assessment are examined including observation, portfolios, performance tasks, and paper-and-pencil tests, including standardized tests. Basic techniques of test construction, item writing, and analysis are included. Standardized norm-referenced tests and statewide testing programs are also examined.

Intermediate Statistics 

Topics and computer exercises address tests of means, partial and part correlations, multiple regression, analysis of variance with planned and post hoc comparisons, analysis of covariance, repeated measures analysis, elements of experimental design, and power analysis.

Evaluation Practice and Methods

This course introduces the process of conducting evaluations from beginning to end. Evaluation is a form of applied social science research focused on systematically assessing the value--merit, worth, or significance--of interventions. Taking an interdisciplinary approach to evaluation, this course draws on scholarly articles and examples from multiple fields including education, public health, social services, and international development and addressing evaluation at various scales including program, organizational, and systems-level evaluations. By the end of the course, students will gain knowledge of how to carry out evaluations; apply this knowledge to develop evaluation plans for real-world interventions; and gain skills to critique existing evaluations supporting their development as informed, critical consumers of evaluations.

Evaluation Theory and Research

Evaluation as a professional practice and academic discipline is characterized by variation in perspectives on what evaluation is and how it should be practiced. This course introduces students to evaluation theory, key debates, and research on evaluation in order to develop students as critical, responsible evaluators and evaluation scholars.

Seminar in Evaluation and Public Policy

The course will examine some issues that arise in educational accountability. The purpose is to develop a deeper understanding of the policy issues and a critical appreciation of the relevant methodological strategies. Topics include the establishment and use of state-specific performance standards under NCLB and the quantification of the relative rigor of those standards; the evaluation of school or teacher effectiveness using so-called value-added models; and the policy evaluation of school reform efforts (such as charter schools) using data from large-scale cross-sectional surveys. The latter two topics both involve causal inferences from observational studies.

Large Scale Assessment: Methods and Practice

Examines large scale assessment procedures internationally (TIMSS and PIRLS) and nationally (NAEP and NCLB). Considers technical, operational, and reporting procedures in view of requirements for reliability and validity as well as resource constraints and political issues. Uses examples from the TIMSS and PIRLS international assessments in mathematics, science, and reading to illustrate procedures for instrument development, sampling, data collection, analysis, IRT scaling, and reporting results.

General Linear Models 

Addresses the construction, interpretation, and application of linear statistical models. Specifically, lectures and computer exercises cover ordinary least squares regression models; matrix algebra operations; parameter estimation techniques; missing data options; power transformations; exploratory versus confirmatory model building; linear-model diagnostics, sources of multicollinearity; diagnostic residual analysis techniques; variance partitioning procedures; dummy, effect, and orthogonal coding procedures; and an introduction to structural equation modeling.

Multivariate Statistical Analysis

This course provides lectures, examples, and lab analyses that address multinomial and ordinal logistic regression models, multiple group discriminant analysis, cluster analysis, multivariate analysis of variance, principal component analysis, factor analysis, and structural equation modeling. We cover various issues related to research design, model building, and the interpretation of the output from SPSS, R, Lisrel, and SAS software programs.

Psychometric Theory I: Classical Test Theory and Rasch Models

Presents a study of theoretical concepts, statistical models, and practical applications in educational and psychological measurement. General topics include the history of measurement, Thurstone and Guttman scales, classical true-score theory, and item response theory. Specific topics include principles of Rasch measurement, parameter estimation procedures, fit statistics, item banking, and computer adaptive testing.

Psychometric Theory II: Item Response Theory

This course presents an advanced study of theoretical concepts, statistical models, and practical applications in educational and psychological measurement. Topics include item response theory, two-parameter model, three-parameter model, methods for estimating latent trait and item parameters, models for polytomously scored items, differential Item Functioning(DIF), test equating , vertical scaling, computerized adaptive testing, standard setting, and multidimensional item response theory models. The IRT software or tools used in this course include R, IRTPRO, BILOG-MG, PARSCALE, NOHARM, DIF related software, STUIRT, ST., EQUATE, etc.

Technology Enhanced Assessment

Computers are widely available in schools and are increasingly used for large-scale testing programs. This course examines cutting-edge applications of computer-based technologies to the technology of testing and assessment. Among the topics explored are validity issues specific to computer-based testing; accessibility, universal design, and computer-based testing; computer adaptive testing; simulation-based and multimedia tests; and computer scoring of writing. The course encourages students to explore ways in which computer-based technologies can be used to enhance assessment and solve challenges to current approaches to student assessment.

Multilevel Regression Modeling

This course introduces students to multilevel regression modeling (aka hierarchical models or mixed effects models) for analyzing data with a nesting or hierarchical structure. We discuss the appropriate uses of multilevel regression modeling, the statistical models that underpin the approach, and how to construct models to address substantive issues. We consider a variety of types of models, including random intercept, and random slope and intercept models; models for longitudinal data; and models for discrete outcomes. We cover various issues related to the design of multilevel studies, model building and the interpretation of the output from HLM and SPSS software programs.

Design of Experiments

This course will introduce experimental design as a paradigm for thinking about the conduct of educational research and evaluation. The goals of this course are to introduce students to the design and statistical principles of the experimental approach to educational research with particular emphasis on the correct analysis of data arising from designed experiments. We will discuss a variety of experimental designs, their advantages and disadvantages, estimation of treatment effects, and significance testing. The topics covered will include the underlying logic of experimental and quasi-experimental designs, regression discontinuity and factorial designs as well as cluster randomized and multi-site trials.

Survey Methods in Educational and Social Research

This course is designed to familiarize students with the strategies, techniques, tactics, and issues in the development and administration of survey instruments. It will emphasize both theoretical, measurement and practical considerations (including reliability and validity, etc.) in the development of attitudinal instruments, and several types of measurement scales will be covered in this class. 

Design of Qualitative Research 

Introduces the foundations and techniques of carrying out qualitative research. Topics include philosophical underpinnings, planning for a qualitative research project, negotiating entry, ethics of conducting research, data collection and analysis, and writing/presenting qualitative research. Requires a research project involving participant observation and/or interviewing.

Dissertation Seminar

This two-semester seminar is designed to assist doctoral candidates in the preparation of a formal doctoral dissertation proposal. All aspects of dissertation development will be discussed (e.g., problem development, human subjects review, final defense). Students will develop and present a series of draft proposals for faculty and student reaction. Depending on the circumstances of the student, an acceptable pre-proposal (Intent) or full dissertation proposal is required for completion of the course.