Research Opportunities

The College of Education’s Office of Research Support provides assistance to graduate students in seeking funding sources and writing and submitting research proposals for funding. You can also find many research opportunities through the college's various research centers and projects.

Faculty members at the College of Education are known for their cutting-edge research and have averaged $20,280,094 in externally funded research grants over the past five years. In fact, between 2001 and 2005, the College of Education saw a 525 percent increase from $646,000 to $3.4 million in research grant funding.

For more information about research opportunities, contact a faculty member who’s research area is of interest to you.

Public Service Opportunities

Between ’01 and ’05, the college witnessed a 128 percent increase in funding of instruction and public service. The College of Education leads all academic units on MU’s campus in instruction and pubic service.

Department research inquiry course

Each department offers a course that focuses on educational inquiry. It provides students with an overview of educational methods and the tools necessary for successful critical thinking in educational investigation. 

The course covers: reading, understanding, and analyzing research, evaluating research design and the results of research studies, synthesizing the finding of various research studies and making generalizations, formulating a conceptual framework for research, identifying research issues and asking appropriate research questions, elements of research design, evaluation research, using the APA guidelines to write up the results of research, and understanding the ethical issues involved in research and the rights of human subjects when conducting research. 

Research Courses for Doctoral Programs

  • Quantitative I – this course focuses on analysis of variance (ANOVA) and include topics such as: simple analysis of variance with follow-up comparisons, factorial designs and their interpretation with follow-up comparisons, repeated measures designs, multivariate ANOVA, ANCOVA, factorial MANOVA, introduction to discriminant analysis, and using a computer for statistical analysis.

  • Quantitative II – this course provides the foundation for understanding regression and correlation analysis.  It includes such topics as simple correlational techniques, simple linear regression techniques including data plotting and testing of parameters, curvilinear and other nonlinear regression models, multiple correlation techniques and testing of parameters, multiple regression and indicator variables in the multiple regression model, canonical correlation, relationship to ANOVA, stepwise multiple regression, and effect coding for regression, and using a computer for statistical analysis.
  • Multivariate statistics – covers multivariate analysis and includes such topics as: discriminant function analysis, principle components and factor analysis, general linear models, scaling techniques, cluster analysis, multidimensional scaling, path analysis, hierarchical linear modeling, and other multivariate techniques used in educational research.

  • Qualitative I – An introductory course in qualitative methods that includes such topics as: 1) philosophical foundations of qualitative methods; 2) data collection strategies, including site selection and sampling; 3) data collection and interpretation strategies (e.g. taking field notes, observations); 4) trustworthiness criteria; 5) computer software programs for data management and analysis; 6) ethical considerations in qualitative research.

  • Qualitative II – (prerequisite Qual 1) – The focus of this course would be in-depth study of a specific qualitative method (e.g. case studies, ethnographic studies, grounded theory) and approaches (e.g. critical theory, dialogical).  Students would be expected to undertake a substantive pilot study using one method.  A major focus of this course would be on preparing qualitative text.
  • Educational Planning and Evaluation – The course addresses the major issues in program planning and evaluation including topics such as: the appropriate uses of various evaluation models; sources and purposes of different types of evaluation data; skills necessary for collecting, analyzing, and interpreting data to make informed program decisions; design of criteria-based evaluation questions; reporting the results of evaluations to internal and external audiences; principles of formative and summative evaluations; performance-based evaluations; and using qualitative and quantitative techniques in conducting evaluations.

  • Advanced elective courses – these courses would cover a variety of special topics.  Some examples include: 1) time series analysis, 2) latent variable/structural equation modeling, 3) growth modeling, changes and developmental analysis, and hierarchical linear modeling, 4) advanced measurement and scaling, and intra-subject replication designs  These course would be offered by faculty who have special talents and interests and be available to advanced doctoral students.