Introductory course in applied descriptive statistics, correlational methods, and linear regression that provides a conceptual and theoretical foundation for more advanced work and a thorough grounding in the use of computers for descriptive statistical analysis and interpretation of results.
Techniques and uses of research in education. Designed to provide the student with the ability to read, understand, and critically evaluate publishedempirical research.
For teachers, counselors, school administrators. Principles of measurement and evaluation; methods of scoring and interpreting tests. Construction and use of teacher-made tests. Statistical concepts basic to understanding and interpreting test data. (Note: this course is offered as combination campus-based and internet-based course.)
Existing and emerging formulations of educational evaluation. Developing operational guidelines for conducting evaluation in educational settings.
An application course that uses modern evaluation models, data collection,statistical analysis, and interpretation of findings to establish the effectiveness and utility of educational programs.
Statistical foundations, classical test theory, reliability, validity, item analysis and norms; selected topics in modern test theory. Designed for those who will develop, evaluate, and select measurement instruments in their professional roles.
Theory, methods, and procedures of survey research as this methodology is applied to problems in education. Sampling from future populations.
Conceptual and mathematical foundations, parameter estimation, tests of model assumptions and goodness of fit, and practical applications of IRT.
Modern techniques for summarizing and visualizing univariate and multivariate data using various statistical and graphical software packages. Covers theories and research on graphics and the perception of visual data.
Introductory course in applied inferential statistics that includes applied probability theory, methods of estimation, and hypothesis testing for a wide variety of applications, and elementary analyses of variance. Concept learning, applications, computer analysis, and computational algorithms are stressed.
Experimental design, analysis of linear statistical models, interpretation of statistical results and research presentation. Analysis of variance, analysis of covariance, and multiple linear regression. Applications in education and the social sciences.
Multivariate normal distribution. Cluster analysis, discriminant analysis, canonical correlation, principal component analysis, factor analysis, multivariate analysis of variance. Use and interpretation of relevant statistical software.
This course will introduce foundational concepts in statistical computing using the R language.
This course will provide a survey of classification models used to identify groups of people from a set of observed variables.
Advanced techniques of research or measurement applied to educational or social and behavioral science problems.
Technical developments and applications in classical test theory, item response theory, generalizability theory, models of selection bias,differential item functioning, and test score equating. (Syllabus is an example only. Topics will change as a function of new developments in educational measurement, assessment, and psychometrics.)
Computer-based testing applications including automated test assembly, item banking, computer-adaptive and multistage testing, web-based testing, large-scale assessment development and support systems, and computer-based performance assessments. Covers state-of-the-art research and developments.
Exploratory and confirmatory factor analysis and multidimensional scaling.Methods of estimation and rotation including the common factor model. Weighted and unweighted MDS.
Advanced topics in item response theory, including maximum likelihood estimation, margninal maximum likelihood estimation, Markov chain Monte Carlo estimation, polytomous item response theory models, partial credit models, graded response models, and nominal models.
ERM 730—Practicum in Educational Research andEvaluation
Field-based and mentored practicum. (Syllabus is NOT available. Students arrange to participate in extended field experiences related to educational research, measurement, applied statistics, or program evaluation,with the consent of their advisor.)
Formulation of statistical models, estimation of structural coefficients using LISREL, estimation of model fit, confirmatory factor analysis models, practical applications.
Structure of hierarchical data, random intercepts, individual change/growth models, applications in meta-analysis, assessing hierarchical models, hierarchical generalized linear models, hierarchical models for latent variables, cross-classified random effects, estimation.
ERM 733—Language Testing
Theoretical and practical issues related to second language testing with special attention paid to the assessment of English as a second language, world Englishes, and foreign languages.
Equating designs, equating and scaling assumptions, design of anchor sets, observed score equating methods, true-score equating methods, standard error of equating, use and interpretation of relevant statistical software.
Multidimensional item response theory models including their estimation, representation, and application. Use of relevant estimation and graphing software discussed.
Theoretical understanding of evaluation design and strengthening of practical program evaluation skills.
Overview of the methodology of case study research; enhancement of students’ skills in using case study methods.