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12 Cards in this Set
- Front
- Back
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Purpose of Evaluation Research: |
- To scientifically determine the impact of a specific program, intervention, new method, or social policy. - Form of Applied vs. Theoretical Research
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Issues of Measurement (Evaluation Research): |
1. Outcomes Measures 2. Experimental Context 3. Specifying Interventions 4. Specifying the Population 5. Operationalizing Success vs. Failure |
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Outcome Measures: |
- Must be able to reliably and validly measure your outcome variable(s). |
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Experimental Context: |
- Must measure aspects of the context on an experiment that possibly may affect the outcome variable. |
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Specifying Interventions: |
- Need to accurately measure the program intervention or the experimental stimulus. |
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Specifying the Population: |
- Must define the population of possible subjects for whom the program is appropriate.
- Also, need to control for other variables such as age, race, etc. |
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Operationalizing Success vs. Failure: |
- Defining Success vs. Failure. - Measuring success and Failure is NOT clear cut. - Often, it comes down to Cost-Benefit Analysis. |
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Types of Evaluation Research Designs: |
1. Experimental Designs 2. Quasi-Experimental Designs 3. Qualitative Evaluations
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Experimental Designs: |
- Randomly assign subject to Control and Experimental Groups, then measure before/after the experimental effect in both groups. - Deals with all the potential problems of Internal Validity. |
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2 Quasi-Experimental Designs: |
1. Time-Series Designs: Involves measurements taken over time with an intervention during the time series. 2. Multiple Time-Series Designs: Measurement of variable(s) over time in different locations or among different groups, ones which received the experimental stimulus (or program) and which did not |
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Qualitative Evaluations: |
- Evaluations can also be less structured and more Qualitative than Quantitative. - Many argue that the most effective evaluation research is one that combines Qualitative and Quantitative components. |
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Guidelines for Presenting Research Results to Non-Researchers: |
1. Know Your Audience 2. Let the Data Answer your Questions 3. Make the Presentation of Data Simple 4. Parsimony in Numbers |
