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Program Evaluation: a Case Study

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Abstract

Program evaluation is very important to establish an organization able to gather information about a certain plan to update, evaluate, start a new program and do an evaluation. The logic models are very important, like a framework of the entire program. The hypothesis is also important in finding out if there are any null hypothesis or any alternates. Individuals who smoke need to know about a campaign that individuals can stop smoking, but it is going to be extremely hard, especially if an individual does not know about the British Columbia campaign about how to quit smoking for the better.

Program Evaluation

Program evaluations are imperative to any organization that wants to improve program initiatives, renovate, evaluations, and to informs participants that a change is coming. Individuals who smoke and want to quit creating a better program evaluation is a great thing. The campaign in British Columbia and smokers rely on an individual’s alertness, the importance of smoking, actions, and defiance of individuals who smoke. (Argosy University, 2018)

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What are the main features of your evaluation design?

Evaluation Design

The main features of my evaluation design are the non-experimental design, the outcome evaluation and the importance of studying over-time would be something to address. The logic model must prove that the program being studied is complete for a program evaluation. The research questions can make or break the design.

How would it be implemented?

Implementation

The campaign for smoking will last a year and implemented in stages. The first stage being in “March to April.” The second stage is “July and August,” and the third stage being in “October and November.” (Argosy University, 2018) Individuals that might have known about the campaign, order did not know, understanding increased, mindset had changed and defiance changes that resulted in behaviors. (Argosy University, 2018)

Media coverage was used to provide information to individuals that might want to quit, and gain assesses to treatment programs that might help individuals to access their behaviors and attitude about smoking. (Argosy University, 2018)

Logic Model

The logic model I created for this campaign was interesting for individuals that smoke. Every logic model is different and constitutes inputs, outputs, and outcome. The smoking campaign in British Columbia and the attitudes and behaviors mostly twenty and thirties can create a plan to have individuals stop smoking altogether, which will sustain their lives for the better.

There are several different logic models interacting with one another. It is like a major road may that contains the situation, inputs, outputs, and outcomes from short-term to long-term, it is what you get from a program and what needs to be changed. (University of Wisconsin-Extension, 2016)

How does the design deal with a possible rival hypothesis?

Hypothesis

There are many hypotheses for a program and some are better than others but talking about a rival hypothesis is trying to find out if there are other hypotheses that may interfere with the main hypothesis of a certain program. Without testing a hypothesis for my program, I can only guess at this time.

The alternant hypothesis is a hypothesis that may become a null hypothesis which can turn into a false positive because the two variables do not go together. Like, smoking and age.

Design

The design should have a conclusion when the research study is created, meaning minor sample performance is acceptable according to (Garcia- Perez, 2012) The concept can include insufficient information examination are sometimes carried out, which leads to a conclusion. The external strength is sought by “observing and measuring dependent variables.” (Garcia-Perez, 2012)

The design is everything and it helps the program to become alive and understand. Researchers must understand the ins and outs of a program to get the benefits and comprehend what is about to take place.

Conclusion

In conclusion having a plan and a logic model in place will help researchers to determine what is valid and what the program is all about, but testing and qualitative or quantitively must be measured to draw some conclusion to understand the plan.

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