Ok, so remember that post about the “why” questions and how they are so important for figuring out where you can actually make change on what seems like an intractable problem? They work just as well on the other end, to help figure out WHAT you’re trying to change.
I’m a big fan of logic models. And I mean a BIG fan. I use them with almost every group I work with. I think about them, I doodle them. I have them in my head when I’m just planning a walk in the park. (‘What will change as a result of this walk in the park?’ I ask myself.)
But yet, somehow the data mural work started and we hadn’t yet developed a logic model. How could that have happened!? And, as I could have predicted (if it hadn’t been my own project and therefore a big blind spot for me) the evaluation tools that we had weren’t really giving us the information we wanted. And Rahul and I didn’t always agree about why we were doing each activity. This is JUST the kind of situation where a logic model can help. So we’ve drafted one.
It hasn’t answered all of our questions yet. We’re still wondering about exactly how visible the underlying data have to be in the final product (and why) and we’re still wondering whether there should be an outcome related to the public’s familiarity with data. But in the meantime, this has clarified a lot for us and now we can make improvements to out next projects. For example,
1. We can revise the pre and post-tests that we use for each activity to capture information about the outcomes that we actually hope to achieve
2. We can make sure to plan activities within each session that will help reach our outcomes
3. We can both give the same answers when people ask us what the data mural project is all about
4. We can use different sections (leading to different outcomes) as a focus for different potential funding sources based on their individual interests
5. We can design our ongoing data collection to explore intermediate and long-term outcomes