Program Evaluation Integrate Data Collection Methods Into Essay

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Program Evaluation Integrate data collection methods into the program evaluation plan.

The data collection method is seeking to integrate qualitative and quantitative research together. It is developing a program that is effective in helping to support smoking cessation efforts. Qualitative research is used to provide background on the study and proven smoking cessation initiatives. For instance, this portion of the research revealed that any effective program will integrate therapy, support groups and medication with each other. The basic idea is to address the chemical and psychological states a person will feel when they are quitting. However, changes in technology are leading to more people using online support. This gives them the flexibility to attend meetings and discuss their problems with counselors 24 hours a day. These shifts are indicating how there are variety of options and tools for having a successful smoking cessation efforts. (Yin, 2009)

The quantitative approach is taking a different perspective when it comes to quitting. It is interested in the way these trends compare with a sample of smokers. The main idea is to determine which programs are the most popular based upon age, gender and racial demographics. In this case, a total of 97 respondents were selected. They ranged from 29 to 79 and the majority of respondents (89.1%) were white males. This helps in determining which programs are the most effective, the rates of successes and corroborate the findings from the qualitative method. (Yin, 2009)

The way the data was collected is part of the evaluation by objectively looking at what is happening from a longer term perspective. This supports those smoking cessation programs that are the most effective and which one produces the best results. Once this takes place, is the point the research is used as a foundation to talk about these programs and the lasting impacts they are having on smokers. (Yin, 2009)

Evaluate the strengths and weaknesses of data collection sources for your program.

The strengths of the program are its ability to maintain objectivity and corroborate the findings with each other. This improves accuracy by confirming the underlying trends with each other. These conclusions will provide insights about how long-term cessation efforts can be established and which programs are the most effective. At the same time, it looks at what different demographics of people prefer and how they can be customized to meet their needs. This improves the success rates by knowing the individual and what is most important to them. Then, they can create a solution which can be customized to guarantee long-term success. (Yin, 2009)

The biggest weaknesses are with the sample that was collected. In this case, the majority of respondents were white males. This does not take into account other factors which could impact someone differently (i.e. racial, gender and economic). These variables can influence the kinds of solutions that are selected and which ones are the most effective. To make matters worse, the sample was very small. This is troubling, as it could skew the results and lead to unsubstantiated conclusions. If this were to occur, researchers could state these programs are effective. Yet, they failed to fully understand which ones could be customized to meet the needs of the individual. This is when the odds increase of them having long-term success with smoking cessation efforts. (Yin, 2009)

The strengths and weaknesses are showing how the research project can provide measurable results and new insights. However, the biggest drawback is the limitations in the size and quality of the sample. In this case, there was no diversity chosen to answer other factors which could affect someone differently. This can make some programs ineffective by failing to understand other characteristics. As a result, the study provides a good foundation for discussing these challenges and possible solutions. This can be used as an initial foundation for other research in determining how to establish smoking cessation efforts. (Yin, 2009)

Determine threats to the data collection process for your plan.

The biggest threat to the data collection process is the sample and subjectivity of researchers. The sample is problematic, as only a specific segment of society was chosen (i.e. white males). This ignores racial, gender and economic demographics. The combination of these factors is contributing to a sense of bias by ignoring areas that are important. This opens the data collection process up to accusations that the study did not provide any kind of measurable results. (Yin, 2009)

At the same time, researchers could be accused of showing favoritism and subjectivity. This is because they decided to use a sample that was exclusively focused...

...

If they wanted to expand their findings, the sample size and selection process would have focused on diversity. The fact that researchers ignored this is illustrating how they were bias and wanted to work with demographics they were most comfortable with. This ignores the reality that they needed to maintain objectivity in the process. Instead, researchers create a program which appeared to achieve some legitimate scientific interest. Yet, the sample only focused on one segment of society and was uninterested on expanding the study. In this aspect, one could argue that the researchers were bias from understanding and setting up the study in this way. (Yin, 2009)
Over the course of time, some could challenge the data collection process and the validity of the research. If this were to happen, there is a probability many peers will discount the research and look at conducting a broader study. This is the point they reduce the quality of the information and the findings. (Yin, 2009)

Recommend appropriate data analysis procedures for your plan.

The methodology will focus on using the mixed method approach. This is when both qualitative and quantitative sources are used to understand the problem. In this case, the qualitative research will identify key trends using previous studies and data were collected. This is used to establish different avenues of smoking cessation and the impact it is having on them. (Yin, 2009)

Quantitative research is used to comprehend the impact of smoking cessation programs on individuals in the 29 to 79-year-old demographic. Their responses will be compared with each other and categorized. Once this takes place, is the point the findings from the study will be compared with other information. (Yin, 2009)

During the process, comparative analysis will be utilized. This is when the information will be compared with each other to identify which programs are most effective. Anything that does not corroborate with each other is placed into a separate category as an anomaly. It will be researched further and listed as a possible limitation in the study. (Yin, 2009)

If this kind of approach is utilized, it will improve accuracy and validity. This is when the findings of the research will be more in depth. In the future, similar projects will take place in order to reach out to colleagues and demonstrate the importance of expanding upon these areas. Over the course of time, this could lead to customized programs that will look at the individual and try to understand how it is impacting them. (Yin, 2009)

A good example of this can be seen with insights from the National Institute of Health which said, "Mixed methods researchers use and often make explicit diverse philosophical positions. These positions often are referred to as dialectal stances that bridge post positivist and social constructivist worldviews, pragmatic perspectives, and transformative perspectives. For example, researchers who hold different philosophical positions may find mixed methods research to be challenging because of the tensions created by their different beliefs. However, mixed methods research also represents an opportunity to transform these tensions into new knowledge through a dialectical discovery. A pragmatic perspective draws on employing "what works," using diverse approaches, giving primacy to the importance of the research problem and question, and valuing both objective and subjective knowledge. A transformative perspective suggests an orienting framework for a mixed methods study based on creating a more just and democratic society that permeates the entire research process, from the problem to the conclusions, and the use of results. Optimally, all studies draw upon one or more theoretical frameworks from the social, behavioral, or biological sciences to inform all phases of the study. Mixed methods studies provide opportunities for the integration of a variety of theoretical perspectives (e.g., ecological theories, complexity theory, stress theory, critical theories, or others)." ("Best Practices," 2014) This is illustrating how the quality of the research will improve by embracing these concepts. Once this occurs, are when the study will be more focused and objective. This reduces arguments of bias by showing how the facts were corroborated with each other.

Distinguish between data of practical significance and data of statistical significance in your plan.

The practical significance is calculating the difference between the estimate and the actual outcome of the program. This helps in objectively analyzing, if it was successful and the way it answered key questions. A statistical significance will vary based upon the sample size. It is used to determine if it was large enough and looked at a number of other factors…

Sources Used in Documents:

References

What is Program Evaluation? (2014). University of Washington. Retrieved from: http://www.washington.edu/oea/services/research/program_eval/faq.html

Best Practices. (2014). NIH. Retrieved from: http://obssr.od.nih.gov/scientific_areas/methodology/mixed_methods_research/section2.aspx

Bradley, J. (1986). Current Empirical Research. Review of Educational Research, 56 (3), 331- 364.

Kirk, R. (1996). Practical Significance. Educational and Psychological Measurement, 56 (5), 746 -- 759.


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