Introduction to the certificate program topics including the meaning of causal evaluation, how it can inform decision-making and continuous improvement processes, and a review of relevant math and statistical tools. S/U Graded.
Survey of research methods facilitating causal inference. Includes basic introduction to randomized control trials and quasi-experimental methods that can be used when a randomized control trial is not feasible. S/U Graded.
EII 604: with minimum grade of C
Use theory to drive analytic decisions and demonstrate how to estimate, interpret, and communicate impact of Randomized Control Trial. Emphasis is on using Ordinary Least Squares regression. S/U Graded.
EII 606: with minimum grade of C
Learn to program and interpret results of applied problems using the quasi-experimental techniques learned in
EII 606, including propensity score matching, difference-in-differences, and regression discontinuity S/U Graded.
EII 607: with minimum grade of C
Students will develop a logic model —a graphical representation that illustrates how the resources and strategies of an intervention are expected to translate into the desired outcomes. S/U Graded.
EII 604: with minimum grade of C
Determine strategies for conducting Randomized Control Trials within schools considering timing, context, generalizability, strengths, and barriers. If a local RTC is not plausible, make use of existing research and evaluations to inform decision-making. S/U Graded.
EII 607: with minimum grade of C and EII 609: with minimum grade of C
Students will apply a practical process to a theory-based framework to plan, implement, and use evaluation to critically examine the implementation of local educational initiatives. S/U Graded.
EII 606: with minimum grade of C and EII 609: with minimum grade of C
Introduction to design principles and software for developing static and interactive data visualizations. Emphasis is on matching communication and data visualization strategies to target audiences. S/U Graded.
EII 604: with minimum grade of C
Framework for developing partnerships among education agencies and research institutions to inform and evaluate policy and innovative practices. Emphasis is on building long-term, sustainable partnerships. S/U Graded.
EII 604: with minimum grade of C
Introduction to identifying and understanding the costs of educational interventions. Overview of how to select the appropriate type of cost study: cost-analysis, cost-effectiveness, or cost-benefit. S/U Graded.
EII 604: with minimum grade of C
A case study approach to identifying costs, calculating cost ratios, and translating the findings into recommendations for decision-making. S/U graded.
EII 614: with minimum grade of C
Survey of research methods facilitating causal inference when a randomized control trial is not feasible. Includes regression discontinuity, difference-in-differences, instrumental variables, and propensity score matching. Familiarity with OLS regression required.
Student will obtain placement on an applied quantitative education research project that builds on themes from
EII 705 such as working with longitudinal data, statistical programming, or policy analysis. S/U graded.
EII 705: with minimum grade of C
An in-depth application to an education policy area of one of four quasi-experimental methods (regression discontinuity, difference-in-differences, instrumental variables, or propensity score matching) or a comparison of multiple methods. S/U graded.
EII 705: with minimum grade of C