In our last post, we assured you that it was possible to complete an evaluation without ever leaving your desk! So as promised, here’s how to conduct a secondary research evaluation in four simple steps.
Remember, in the scenario in our last post, you are a youth services librarian at a rural public library that serves a population of 4,000. You want to know if your summer learning program is effective at engaging youth with developmentally enriching content (our evaluation question). You don’t have the time or resources to go out and collect your own data, so you decide to conduct secondary research instead to help you make a decision about how to improve your summer learning program. In our last post, we talked about the different ways you can conduct secondary research. Now we’re going to apply the multi-data set approach. Here’s how you can do that in four simple steps.
- Identify your evaluation question
We’ve already determined that our evaluation question is: do summer learning programs engage youth with content that is developmentally enriching? If you need help determining your own evaluation question, you can revisit our post on the topic.
- Identify a secondary data set (or sets)
Review the existing literature on your topic of interest. In our last post, we identified different external and internal data sources that you can investigate. You may find other libraries, organizations, or agencies that have explored your topic and collected data. Reach out and ask for permission to use their data if necessary. For this example, let’s say we found this publication of key research findings on public libraries’ role in youth development. To get a well-rounded understanding of your topic and enough data to analyze, you’ll probably need to find multiple data sets. For the purpose of this post, we’ll just look at one.
- Evaluate secondary data set
Congrats, you’ve chosen a data set! Sometimes that can be the hardest part. Now we need to evaluate whether we chose the right one. To do so, we’ll try to answer the questions below. If you need additional help understanding how to answer these questions, read this first.
- What was the aim of the original study?
- Who collected the data?
- Which measures were employed?
- When was the data collected?
- What methodology was used to collect the data?
Based on what we found, the data set we selected comes from a reliable source and is relatively recent. Some of the libraries in the study also serve a population that is close in size to our own. However, the aim of the original study is a little different than ours (the role of libraries as a whole on youth development). Therefore, we might want to find an additional data set specifically on summer learning to help us answer our evaluation question. If one of the public libraries who participated in the study has a similar population or demographics as our library, we could also reach out to them directly and ask to see their data.
- Analyze secondary data set
Pick the variables from your data set that are most relevant to your evaluation question. You may also need to recode variables. For instance, maybe the data set includes a variable for school district, but that’s not important to you. You’re more interested in seeing if there’s a correlation between poverty and youth development. Therefore, you can recode the school district variable by percentage of people who live below the poverty line in each district (using another data set in tandem!). Here’s a short video on how to recode variables in Excel. Once you’ve got all your ducks in a row, you’re ready to employ all your statistics mastery (mean, median, mode, correlation, etc) to draw conclusions from your data.
There you have it! An evaluation without ever leaving your desk. As always, if you have any questions or comments, please feel free to reach out to us at LRS@LRS.org. In our next post, we’ll cover another evaluation methodology, so stay tuned.