Assessing Program Impact: Key Concepts
Assignment Instructions
Complete a short essay 700-1000 words of the key points to chapter 9 in the textbook, and some application of the week's material. This should allow you to demonstrate your understanding of the material. DO NOT use the summary points at the end of the chapter, instead focus on applying your knowledge. The summary points may guide you in figuring out what is important but, maybe something else caught your attention that you would like to talk about instead. Remember to use APA format.
You can:
find a policy and apply key concepts
apply your knowledge of the materials in other ways.
NOTE: Some of the information (i.e., key concepts) is necessary to define to demonstrate your understanding of the module material.
Rossi, P. H., Lipsey, M. W., & Freeman, H. E. (2014). Evaluation: A systematic approach. 7 th edition. Sage publications.
Chapter 9: Assessing Program Impact: Alternative Designs
OR
Assessing Program Impact: Alternative Designs
Evaluators are expected to accurately describe the effects of a project on a target group using a reliable measurement. The effect of a project can be defined as the difference between the outcome of a project and the outcomes the target group can achieve without the project. Bias results when the measurement of the program outcome or the outcome without the program is lower or higher than the actual value (Rossi, Lipsey & Freeman, 2014). In this assignment, I will discuss the concepts in chapter nine of the coursebook: Assessing Program Impact: Alternative Designs. Specifically, I will evaluate how the ideas in the chapter can be applied to Arizona Cash Assistance Program. The initiative was developed to provide financial assistance to needy families to enable them to be self-sufficient.
There may be bias in measuring the observed effect for targets exposed in a program if the evaluator does not use measures that can respond to different outcome levels that may appear among the targets. Bias in impact assessments is mostly caused by research designs that systematically overestimate or underestimate unobserved outcomes that would have happened without exposing the target population to the intervention (Rossi, Lipsey & Freeman, 2014). For example, suppose, the Arizona Cash Assistance Program officials are evaluating the ability of children from needy families to know how to read and write some words. They can measure children’s reading and writing capabilities before and after giving the funds to go to school and then get the outcome. However, the children’s reading and writing capabilities may be improved by some factors other than education, like interaction with other children. Therefore, there may be bias if the amount of improvement in the ability of the children to read and write without being exposed to the program is included in the estimate.