Advanced Program Evaluation
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Learners will take on the role of a staff member at the Middleton County Health Department who is tasked with helping to develop an evaluation plan for an obesity-prevention program recently launched in Middleton County. Using the CDC Program Evaluation Framework, learners will connect each step of the framework with a section of the evaluation plan, going into detailed discussion about: selecting and incorporating stakeholders in the evaluation process, developing relevant evaluation questions, designing an evaluation study and using standard notation, choosing a sampling strategy, and thinking through limitations and threats to validity. Additionally, learners will review strategies for conducting rigorous evaluations within constraints of budget, time, and resources.
Through prior training or experience, trainees are expected to have background knowledge of the following topics:
- Social science research methods
- Logic models
- Process and outcome evaluation
- Evaluation questions
- CDC Framework for Program Evaluation in Public Health
- For those without this background knowledge, it is recommended that you complete the following three trainings: Program Development & Evaluation, Introduction to Logic Models and Evaluating a Public Health Program.
Who should take this course?
- Tier 1 - entry level public health professionals (i.e. individuals that have limited experience working in the public health field and are not in management positions)
- Tier 2 - individuals with management and/or supervisory responsibilities
- MPH students
What You'll Learn
- Appreciate that a comprehensive evaluation plan addresses a program logic, stakeholders, evaluation questions and evaluation design.
- Assess advantages and limitations of evaluation designs, including randomized, quasi-experimental and pre-post designs.
- Appraise and compare options for data collection methods, measures and sampling strategies.
- Identify and address associated threats to validity.
- Identify strategies for addressing budget, time, data and political constraints in evaluation practice.