Overview of ERM Courses
ERM offers a wide range of courses pertaining to research methodology, applied statistics, educational and psychological measurement, program evaluation, statistical modeling, and psychometrics. Brief descriptions and syllabi for ERM courses are provided on the Course Syllabi tab of this web page. A schedule of courses offered over the next several years can be downloaded from the Schedule of Courses tab of this web page.
Research Methodology and Statistics
ERM 604: Methods of Educational Research
ERM 668: Survey Research Methods in Education
ERM 675: Data Presentation and Reporting
ERM 680: Intermediate Statistical Methods in Education
ERM 681: Design and Analysis of Educational Experiments
ERM 682: Multivariate Analysis
ERM 685: R for Education and the Social Sciences
ERM 693: Seminar in Advanced Research Methods
ERM 731: Structural Equation Modeling
ERM 732: Hierarchical Linear Modeling
Measurement, Assessment, and Psychometrics
ERM 600: Validity and Validation
ERM 605: Educational Measurement and Evaluation
ERM 633: Language Assessment and Testing
ERM 636: Advanced Studies in Second Language Testing
ERM 667: Foundations of Educational Measurement Theory
ERM 669: Item Response Theory
ERM 726: Advanced Topics in Educational Measurement
ERM 727: Computer-Based Testing: Methods and Applications
ERM 728: Exploratory and Confirmatory Factor Analytic Methods for Scale Construction
ERM 729: Advanced Item Response Theory
ERM 734: Equating
ERM 735: Multidimensional Item Response Theory
ERM 642: Evaluation of Educational Programs
ERM 643: Applied Educational Evaluation
ERM 730: Practicum in Educational Research and Evaluation
ERM 742: Advanced Topics in the Evaluation of Educational Programs
ERM 750: Case Study Methods In Educational Research
Syllabi of ERM Courses
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 published empirical 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.)
ERM 633—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.
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, marginal 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 and Evaluation
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.
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.
Schedule of Future Course Offerings
For students and student advisors planning course sequences, it is often useful to have a schedule of anticipated ERM course offerings for the upcoming years. To meet this need, we have constructed a document containing the anticipated ERM course offerings for the next several years. It is important to note that this is a list of expected future course offerings, and deviations from this schedule may occur depending on the availability of faculty to teach courses and student enrollment numbers.
You can download the tentative schedule of future ERM course offerings by clicking here.