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Courses - Spring 2020
EDMS
Measurement, Statistics, and Evaluation Department Site
EDMS451
Introduction to Educational Statistics
Credits: 3
Grad Meth: Reg, P-F, Aud
GenEd: FSAR
Restriction: Sophomore standing or higher.
Credit only granted for: BIOM301, BMGT230, CCJS200, ECON230, ECON321, EDMS451, GEOG306, GEOL351, GVPT422, INST314, JOUR405, PSYC200 or SOCY201. (These courses do not necessarily meet the same major requirements-check with your advisor to see which of these courses will count for your major).
Introduction to statistical reasoning; location and dispersion measures; computer applications; regression and correlation; formation of hypotheses tests; t-test; one-way analysis of variance; analysis of contingency tables.
EDMS626
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS623.
Theory, development, and applications of various affective, cognitive, or behavioral measurement instruments and procedures, including questionnaire and test items, observational protocols, and cutting-edge innovative game and scenario-based assessments.
EDMS645
Quantitative Research Methods I
Credits: 3
Grad Meth: Reg, Aud, S-F
Research design and statistical applications in educational research: data representation; descriptive statistics; estimation and hypothesis testing. Application of statistical computer packages is emphasized.
EDMS646
General Linear Models I
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS645; or an equivalent introductory statistics course.
A first post-introductory inferential statistics course, with emphasis on analysis of variance procedures and designs from within the general linear modeling framework. Assignments include student analysis of education and related data; application of statistical software packages is emphasized.
EDMS647
Causal Inference and Evaluation Methods
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: Must have completed or be concurrently enrolled in EDMS651.
Counterfactual (potential outcomes) framework for causal inference, design/analysis strategies for confounder control, and specific best-practice applications to the evaluation of programs.
EDMS651
General Linear Models II
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS646; or students who have taken courses with comparable content may contact the department.
Multiple regression and correlation analysis; trend analysis; hierarchical and stepwise procedures; logistic regression; software for regression analysis.
EDMS722
Structural Modeling
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS657.
Statistical theory and methods of estimation used in structural modeling; computer program applications; multisample models; mean structture models; structural models with multilevel data (e.g., sampling weights, growth models, multilevel latent variable models).
EDMS724
(Perm Req)
Modern Measurement Theory
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS623 and EDMS651.
Theoretical formulations of measurement from a latent trait theory perspective.
EDMS738T
Seminar in Special Problems in Measurement; Assessment Engineering
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS 623

This is a graduate-level seminar course in Assessment Engineering (AE). AE is a multidisciplinary field integrating theories and methods from education, business, psychometrics, statistics, and computer science in order to address current issues of assessment as well as to devise innovative assessment products and services. Emphasis will be placed on modern/digital transformations of assessment, incorporating technologies (e.g., Machine Learning) with psychometric advancements (e.g., Automatic Item Generation, Computer Adaptive Formative Assessment, and Learning Analytics Platform). EDMS 623 is a prerequisite; experience with modern measurement theory (e.g., EDMS 724) is helpful, but not required.
EDMS787
(Perm Req)
Bayesian Inference and Analysis
Credits: 3
Grad Meth: Reg, Aud, S-F
Prerequisite: EDMS651.
Credit only granted for: EDMS769B or EDMS787.
Formerly: EDMS769B.
Models and model fitting methods commonly used in Bayesian Inference, such as Markov Chain Monte Carlo methods (e.g., Gibbs, Metropolis Sampling), with applications within and beyond the social and behavioral sciences. Analytical and philosophical differences between Frequentist and Bayesian statistics will also be highlighted.
EDMS798
(Perm Req)
Special Problems in Education
Credits: 1 - 6
Grad Meth: Reg, Aud, S-F
Prerequisite: permission of department.
Contact department for information to register for this course.
EDMS799
Master's Thesis Research
Credits: 1 - 6
Grad Meth: S-F
Contact department for information to register for this course.
EDMS889
Internship in Measurement and Statistics
Credits: 3 - 8
Grad Meth: Reg, Aud, S-F
Contact department for information to register for this course.
EDMS898
Pre-Candidacy Research
Credits: 1 - 8
Grad Meth: Reg, S-F
Contact department for information to register for this course.
EDMS899
(Perm Req)
Doctoral Dissertation Research
Credits: 6
Grad Meth: S-F
Contact department for information to register for this course.