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4.0 Glossary of Evaluation Terms
The following is a list of terms that you will need to
know when planning and implementing your own
Experimental design An experimental design is one in which the participants to the intervention group and the control group (the group that does not receive the intervention) are assigned randomly. This is often called the “gold standard” in evaluation research because it is the best way to isolate program effect and cut down on biases that might confound evaluation results. It is also often the hardest design to achieve in real world settings, such as the classroom. Experimental evaluations are best used in the following environments: (1) for programs not in early stages of development (e.g., you must have some idea about the kinds of questions to ask), (2) in environments that are conducive to randomization (e.g., where you have the ability to randomly select students or teachers for program activities), and (3) as long as ethical considerations have been met (e.g., one group is not harmed by exposure or lack of exposure to the intervention). measure. have participated in the program in question). Outcome measures from intervention groups are typically compared with the outcome measures of one or more control groups. In the matched design, an intervention group is typically selected first, then a control group is purposively selected that will not receive the intervention and that matches identified characteristics of the intervention group. Knowing which characteristics to match for is important with this design, which because of this is subject to selection bias. at one time. you want to be as
representative of your population as possible. has been administered and after the intervention has had time to take effect. The main drawback of this design occurs when the target group cannot be controlled for other
effects that might impact the before and after measurements. measure in an evaluation is the size of the effect of the intervention in your sample group. The purpose of an impact assessment is to isolate and measure program effect.
Quasi-experimental design design. In quasi-experimental designs, participants who receive the intervention are compared with a non-random control group. Quasi-experimental designs
might include a pre-post comparison, a matched comparison, or a
time-series design. In random assignment, every participant in a target population should have the same probability of being selected for either group. Random assignment is the ideal way in evaluation research to isolate program effect, but in some settings random assignment is not possible, in which case you
may choose for a quasi-experimental design. researcher. program evaluations, researchers want to reduce the possibility of biases that might skew the results of an impact study by using randomized or
rigorous comparison sample selection techniques. differences between intervention and comparison groups. Random sampling and other methods of rigorous sampling techniques are used to control for selection bias. the intervention has been administered and multiple measurements are taken of the same target group after the intervention has had time to take effect. Time-series designs do not have to measure the same respondents, but should measure the same target group multiple times after an intervention occurs. This design is good for measuring long-standing trends. to measure. There are many different kinds of validity that are important to control for. Validity can be controlled for by either choosing a random sample or by using several different measures for the same concept. To control for validity, researchers should ensure that evaluation questions clearly correspond to the criterion being measured; when in doubt, use several different sources or methods for one concept; and make sure that evaluation questions taken together cover the wide range of possibilities of the target concept.
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