The Certificate in Analytic Evaluation Methods (CAEM) is designed to help evaluators become more proficient in the use of a variety of technical evaluation designs and analytic approaches.

The CAEM is intended for evaluators seeking to further their technical knowledge, understanding, and expertise in the area of quantitative and/or qualitative methods. We recognize the need for practicing evaluators to have knowledge of both methodological approaches and how to mix them.

For the required thirty days of coursework, candidates for the CAEM may choose from courses focusing on quantitative and qualitative evaluation approaches. However, at least four days of instruction must be completed from courses identified as qualitative and at least four days of instruction must be completed from courses identified as quantitative.

Completion of the first-level Certificate in Evaluation Practice (CEP) before beginning the CAEM is strongly recommended, but is not mandatory. Two courses required for the CEP are also required for the completion of the CAEM.

There is also overlap in terms of the elective courses that satisfy the CEP, CAEP and the CAEM. Many CAEM candidates partially fulfill the CAEM requirements by completing the CEP and CAEP. Courses required for the completion of the CEP also satisfy requirements for the CAEM.

University Policies

Policies detailed in the current Policies and General Information Bulletin apply.

Admission Requirements

Admission requirements are detailed in the Admissions section of the current Policies and General Information Bulletin.

Required Courses

Basics of Program Evaluation OR Basics of Program Evaluation: Culturally Responsive and Strengths-Focused Applications (3 days)

Evaluation Research Methods (3 days)

Elective Courses

Quantitative Focus

Applied Measurement for Evaluation (2-3 days)

Applied Regression Analysis (3 days)

Applied Statistics for Evaluation (4-5 days)

Comparative Effectiveness (1 day)

Hierarchical Linear Modeling (1 day)

Intermediate Cost-Benefit and Cost-Effectiveness Analysis (1 day)

Introduction to Data Analysis for Evaluators and Applied Researchers (2 days)

Introduction to Machine Learning for Evaluators (2 days)

Introduction to R Programming for Data Analysis and Visualization

Linking Evaluation Questions to Analysis Techniques (3 days)

Practical Meta-Analysis: Summarizing Results across Studies (2 days)

Quantitative Methods (2 days)

Social and Organizational Network Analysis (2 days)

Qualitative Focus

Case Studies in Evaluation (2 days)

Intermediate Qualitative Analysis (2 days)

Qualitative Data Analysis (2 days)

Qualitative Evaluation Methods (2 days)

Using Program Theory and Logic Models (2 days)

Qualitative-Quantitative Applications

Making Evaluation Data Actionable (2 days)

Mixed Method Evaluation Approaches (2 days)

Sampling (1 day)

Outcome and Impact Evaluation (3 days)

Design & Method

 Creating and Implementing Successful Evaluation Surveys (3 days)

Culture, Equity, and Evaluation (2 days)

Evaluating Training Programs and MEL (Monitoring, Evaluation, Learning) Initiatives (3 days) OR Evaluating Training Programs: Frameworks and Fundamentals (2 days)

How to Enhance the Learning Function of Evaluation: Principles and Strategies (2 days)

Needs Assessment (1/2 days)

Policy Design and Evaluation Across Cultures (2 days)

Presenting Data Effectively (2 days)

Principles-Focused Evaluation (2 days)

Systems-based Culturally Responsive Evaluation (SysCRE) (3 days)

Using Non-experimental Designs for Impact Evaluation (2 days)