In our last post we introduced you to the dynamic data duo—quantitative (number) and qualitative (story) data. Like any good superhero squad, each have their own strengths and weaknesses. Quantitative data can usually be collected and analyzed quickly, but can’t really yield nuanced answers. Qualitative data is great at that! However, it often takes a lot of time and resources to collect qualitative data. So just like Batman and Robin, who balance out each other’s strengths and weaknesses when they’re together, both can also have successful solo careers. This post will walk you through a simple process to determine which data hero is right for the job!
Step 1: What is your evaluation question?
Let’s say we’re doing an evaluation where we want to find out if attending storytime helps caregivers use new literacy skills at home. If we go up to every caregiver and simply ask them, we’ll get a lot of yes/no answers, but not a whole lot of details. For example, imagine if we asked you right now: “Is this blog series helping you use new evaluation skills at work?” You might respond: “Uh…I don’t know. Maybe?” It’s a hard question to answer accurately. Often the evaluation question is too complex to directly ask participants.
Step 2: Break your evaluation question down into simple questions.
Imagine calling up the Justice League and asking, “Hey, can you save the world?” They might answer yes, but will we know if they have the right skills or perhaps have other plans today? Similarly, our evaluation questions are often broad and abstract. We can’t always ask it outright and get a useful answer. So let’s look at some ways we can break our evaluation question down into simpler questions.
As a reminder, our evaluation question is “does attending storytime help caregivers use new literacy skills at home?” Go word by word and see if you can come up with additional questions that would break the concepts down further. For instance, “does attending…” What are we assuming/what don’t we know?
- Did the caregiver attend a storytime session?
- Why or why not?
- How many times did a caregiver attend a storytime session?
- Which storytime sessions did the caregiver attend?
Continue on with the rest of the evaluation question, keeping in mind you might not come up with simpler questions for every word or phrase.
- Who are the caregivers?
- Were they already using the literacy skills taught during storytime at home prior to attending a storytime?
“New literacy skills”
- Are caregivers learning new literacy skills during storytime? (If caregivers aren’t learning new literacy skills at storytime, they can’t then use those skills at home!)
- Why or why not?
- What new skills are they learning?
- How many new skills are they learning?
- Do caregivers use new literacy skills from storytime at home?
- Why or why not?
- How often do they use new literacy skills from storytime at home?
Step 3: Determine if each sub-question can be answered with numbers or a story
Go back through your list of sub-questions and try to answer each one with a number. Can you do it? If so, the question would give you quantitative data. If not, it might be a qualitative question.
Let’s look at the question, “What new literacy skills are caregivers learning during storytime?” We need words to answer this question, not numbers—right? Not necessarily. We could create a list of 10 literacy skills that we taught during storytime and ask caregivers to check which ones they learned. By creating these parameters, we’re limiting the response options to a finite quantity (10 possible choices) and can count how many people choose each skill. This process transforms what would be an open-ended question yielding qualitative data into a question yielding quantitative data.
You can generally apply this process to questions that either have a finite number of options or where a likert scale is appropriate. However, there are numerous (no pun intended) cases where you’ll want more nuanced, qualitative answers. For instance, try answering the question, “Why did you attend storytime today?” with a number! We could still create a list of possible answers, but it’s likely that someone would look at those choices and feel like none of them really fit. If we want to better understand our caregivers’ reasoning, then we don’t want to limit their responses. We want a story—we want qualitative data.
Step 4: Batman or Robin? Or both?
Now that you’ve classified your questions as quantitative or qualitative, do you have the means (capacity, resources, etc.) to collect data on all of them? Remember the pros and cons of each data type and review which questions are most important to you. Are a majority of them qualitative or quantitative? Knowing which type of data you need to collect will help you decide which data collection method to use. Our next several blog posts will address the different data collection methods you can use and their pros and cons, so keep reading!