Research & Measurement (EDRM)
The construction and use of teacher-made tests; descriptive statistics, measurement error, norms, and interpretation of scores; types of standardized instruments for use in elementary and secondary schools.
Concepts and methods of conducting research in education. Admission to graduate standing.
Methods of statistical inference, including additional topics in hypothesis testing, linear statistical models, and non-parametric analyses.
Introductory course in statistics for graduate students in education and the other social sciences. Central tendency and variability, normal distribution, simple correlation and regression, z and t tests for one and two samples, and the chi-square test. Use of statistical software.
Continuation of Educational Statistics I. Inference for one and two samples, factorial designs, repeated measures designs, and multiple regression. Use of statistical software.
Applied nonparametric statistics in education and the social sciences. Distribution-free inference for repeated measures and factorial designs; logistic regression and log-linear analysis. Use of statistical software.
The study and practice of mixed methods research. The integration of qualitative and quantitative approaches and methods in research practices. Emphasis on educational research and settings with consideration of other social science fields as needed.
The history of educational and psychological measurement. Consideration of concepts such as validity and reliability of educational and psychological measures and the rationale of the development and use of instruments for educational purposes.
Consideration and the construction of educational and psychological tests and measurement instruments.
Emphasis in the linkages between curriculum, instruction, and assessment, and the development of assessments for learning outcomes. Methods include observations, interviewing, performance assessments, portfolios, and classroom tests.
Topics in educational surveys: design of questionnaires, sampling, data collection, treatment of non-responses, survey interviewing, randomized response techniques, data tabulation, and graphical presentation. Use of statistical software.
Statistical techniques and theoretical concepts involved in educational and psychological measurement. Analysis and interpretation of test data, equating of equivalent forms, latent trait theories and models, multiple matrix sampling, and issues related to criterion-referenced testing.
Supervised research experience in a school, state agency, department or bureau of the University, or cooperating institution.
Analysis of grant and contract functions in government agencies; proposal writing; legal and fiscal requirements of grants administration.
Cross-listed course: POLI 755
Concepts and application of designing research in education.
Emphasis on the development of an understanding of the role of inferential statistics in educational experimentation, a working knowledge of the common tests in statistical analysis, and the student’s ability to design and execute experiments involving application of the statistical tests.
Advanced quantitative methods course in multilevel data analysis. Covers theoretical grounding, applications in the social sciences, and model building.
Advanced statistical applications including partial and multiple correlational methods, multiple regression, multivariate analysis of variance, discriminant analysis, and canonical correlation. Use of statistical software.
Theory, methodology and practice of qualitative research in educational settings. Students will conduct research in applied settings using qualitative data collection methods including observation, interviews, focus groups, and document analysis.
Examination of biography as a form of educational research and scholarship.
Theoretical and empirical issues in qualitative and/or quantitative methods in educational research. Content varies; topics and credit announced in advance. May be repeated for up to 12 hours of credit.
Study of advanced concepts, principles, techniques, and issues in structural equation modeling (SEM) and the latent variable framework.
Topics involved with major issues in the planning and conducting of significant research in education. Several faculty members participate; a forum is provided in which candidates may present for analysis original research designs primarily related to their dissertations.