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Mixed-Methods Evaluation of Mentorship.

Mixed-Methods Evaluation of Mentorship.


Title of Program: Youth Mentorship Program

Brief Description: The Youth Mentorship Program is a community-based initiative aimed at providing mentorship and support to at-risk youth in the local community. The program pairs adult mentors with young individuals who may be facing various challenges, such as academic difficulties, behavioral issues, or family problems. The mentors engage in one-on-one sessions, group activities, and educational workshops to help guide and empower the youth towards positive life choices and personal growth.

Type of Evaluation and Research Question: I am conducting a formative evaluation to assess the effectiveness of the Youth Mentorship Program in improving the self-esteem and academic performance of at-risk youth.

Data Source: I will be using both quantitative and qualitative data sources to answer my research question. The quantitative data will come from pre- and post-program surveys administered to both the youth participants and their mentors. The qualitative data will be gathered through semi-structured interviews with a subset of program participants.

Analysis Strategies for Quantitative Data: For the quantitative data, I will employ various analysis strategies. Firstly, I will examine the distribution and frequency of self-esteem scores and academic performance metrics (e.g., GPA) before and after participation in the program. This will involve conducting descriptive statistics, such as means, medians, and standard deviations. Additionally, I will employ paired t-tests to assess whether there are statistically significant improvements in self-esteem and academic performance over time. To visualize the findings, I may create bar charts or histograms to illustrate changes in these variables.

Coding Process for Qualitative Data: For the qualitative data, the coding process will involve identifying key themes related to the experiences and perceptions of both youth participants and mentors. I will need to code for themes such as changes in self-esteem, academic motivation, mentorship effectiveness, and barriers to success. To increase the validity of my findings, I will use a coding framework that involves multiple coders who will independently review and code the interview transcripts. I will also engage in member checking, where I share preliminary findings with participants to ensure their perspectives are accurately represented.

Limitations of Data Source: While this mixed-methods approach provides a comprehensive view of the program’s impact, it has some limitations.

For quantitative data, it may not capture the full complexity of the mentorship experience or the nuances of the changes in self-esteem and academic performance. Quantitative data can tell me if there is an improvement, but it may not reveal why or how these improvements occurred.

For qualitative data, the sample size of interviews may be limited, which could restrict the generalizability of the findings. Additionally, qualitative data is inherently subjective, and there may be bias in how participants recall their experiences or respond to interview questions.

In summary, the data sources I have chosen allow for a multifaceted assessment of the Youth Mentorship Program’s impact on at-risk youth, but they do have limitations in terms of providing a complete understanding of the mechanisms behind any observed changes.

Mixed-Methods Evaluation of Mentorship.





With evaluation proposals, you aren’t analyzing data or writing an analysis plan. However, as you design an evaluation proposal, it’s good to think about how you will use your data to answer your research questions. This is a good step to help avoid collecting unneeded data and to avoid getting to the end of data collection and wondering, “Now what do I do?”

BEFORE YOU ANSWER THE QUESTIONS BELOW: Consider your evaluation proposal, the research question(s) you are proposing to answer, and the kind(s) of data you are proposing to collect. Reflect on how you might use the data you are collecting to answer your research question(s).

For this exercise, pick ONE research question from your proposal and ONE data source and answer the questions below. Your answers should be in essay format and should be free from spelling and grammatical errors.

To refresh my memory, remind me of the name of the program and briefly explain what they provide.

What kind of evaluation are you doing and what is your research question?

  1. What data source are you using to answer this question? Is it quantitative (e.g., survey, administrative data) or qualitative (e.g., interviews, focus groups)?
  2. Based on the kind of data, answer the appropriate question below.
  3. If you’re using QUANTITATIVE data, what kind of analysis strategies might you use? For example, would you be looking at the distribution or frequency of a variable(s) at a single time point? Would you be comparing the distribution or frequency over time? Would you be looking at relationships between two variables? Would some kind of visual make sense, such as a table, bar chart, histogram, etc.?
  4. If you’re using QUALITATIVE data, what might your coding process look like? What kinds of things would you need to code for? What kinds of themes might you expect to see? How might you increase the validity or trustworthiness of your findings?

Now that you’ve thought this through a bit, what limitations might this data source have for answering your research question? In other words, what (if anything) CAN’T this data source tell you about your research question?

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