PSY-FPX5140 covers program evaluation as a distinct methodological discipline — determining whether an intervention or program genuinely produces its intended effects, not simply whether it was well-implemented.
Program evaluation models
PSY-FPX5140 covers major evaluation models — formative evaluation (assessing and improving a program during implementation) vs. summative evaluation (assessing overall effectiveness after completion) — and logic models that map a program's inputs, activities, outputs, and intended outcomes.
Evaluation methods and stakeholder considerations
The course covers selecting appropriate evaluation methods (quasi-experimental designs when true randomization isn't feasible, mixed-methods approaches) and navigating the political and stakeholder dynamics inherent in program evaluation, since evaluation findings can have real consequences for program funding and staff.
Key topics in PSY-FPX5140
- Formative vs. summative program evaluation
- Logic models: inputs, activities, outputs, outcomes
- Quasi-experimental designs for real-world program evaluation
- Mixed-methods approaches to program evaluation
- Stakeholder dynamics and the politics of evaluation findings
- Communicating evaluation findings to non-research audiences
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Worked example: building a logic model for a mental health program
- Inputs: Funding, trained counselors, program curriculum
- Activities: Weekly group counseling sessions delivered over 12 weeks
- Outputs: Number of sessions delivered, participant attendance rates
- Outcomes: Measured reduction in participant depression/anxiety scores at program completion
- Evaluation use: The logic model clarifies exactly what should be measured (outcomes) versus what's simply program activity tracking (outputs) — a common point of confusion in evaluation design
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Frequently asked questions
Outputs are measures of program activity itself — how many sessions were delivered, how many people attended, how many materials were distributed — while outcomes are measures of the actual change or impact the program was designed to produce in participants, such as reduced symptoms, improved skills, or changed behavior. PSY-FPX5140 teaches this distinction carefully because it's a common and consequential evaluation error to report strong outputs (high attendance, many sessions delivered) as if they were evidence the program worked, when outputs only demonstrate that the program was implemented as planned — they say nothing directly about whether the program actually achieved its intended outcomes, which requires separately measuring the actual change in participants, not just the activity level of the program itself.
True randomized controlled experiments require randomly assigning participants to a treatment group and a control group, which is often not ethically or practically feasible in real-world program evaluation — it may be unethical to deny a potentially beneficial program to a randomly selected control group, or practically impossible to control which specific community members choose to enroll in a voluntary program. PSY-FPX5140 teaches quasi-experimental designs — such as comparing outcomes before and after program implementation, or comparing program participants to a naturally occurring (non-randomized) comparison group — as practical alternatives that still allow for meaningful evaluation of program effectiveness, while requiring more careful attention to potential confounding factors and alternative explanations that a true randomized experiment would have controlled for through randomization alone.