The Logic Model: Take it one step at a time
By on September 9, 2020 in Between a Graph and a Hard Place
When your organization designs a program, service or experience, it’s helpful to think intentionally. What do you hope happens? How would you know if it did? We wrote about determining the outcomes for your efforts last time. Identifying outcomes is an important first step in planning and evaluating a program, service or experience. What do you need to do after you’ve identified outcomes? It’s helpful to have a model to guide you through your questions, what you hope will happen, how to best collect data, and how it all connects. There are different types of guides for this process in the...

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What’s your goal here?
Every day we assess the world around us. We ask ourselves whether that decision we made was a good idea, what makes that person trustworthy, why we should or should not change something. We form a question in our head, collect data, analyze the information, and come to a conclusion. In short, we are all experienced evaluators!   However, that doesn’t mean setting up an outcome-based evaluation is a cake walk. It’s important to apply structure to the subconscious process occurring in our head. So where should you start? At the end. That might sound counterintuitive, but the first step in an...

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Finding your way: the difference between research and evaluation
By on August 12, 2020 in Between a Graph and a Hard Place
Have you ever stayed up late, staring up at the night sky, wondering “What is the difference between evaluation and research?” No?! Well, even if you haven’t lost sleep pondering this, we think it’s an important topic. Why? In this blog series, we’ll be focused on how to do an evaluation: how to determine the value and impact of programs, services, and experiences. At the same time, we’ll be talking a lot about methods from social science research because those are our tools for collecting and analyzing data.  Knowing how evaluation and research relate to each other gives you a better...

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Between a Graph and a Hard Place Chapter Two: Do it yourself
Research can be a scary word that comes with a lot of fear about our own skills. We think of experts conducting field work, gathering data, and writing long, technical reports. Like reading a foreign language, it’s easy to feel ill-equipped for deciphering what it all means. Chapter one of Between a Graph and a Hard Place gave you the lexicon for understanding existing data and research. We covered a myriad of topics from checking sources to reading data visualizations that you can find here in case you missed any. Now, we’re excited to introduce chapter two of our blog series...

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Your Ruby Slippers: five key data takeaways
Hi there, readers! We have so enjoyed having you on this data journey with us. The posts we’ve shared since March are an introduction to data literacy, and we’re wrapping up that theme today. Fear not! This series—Between a Graph & a Hard Place—isn’t going anywhere. We’re just starting a new theme, like the next chapter in a book. (We’re data people, but who can resist a book metaphor?)   We hope that you’ve learned something—preferably lots of things—and will join us on the next leg of our journey. Based on surveying you, our readers, the new direction we’re taking is to...

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Visualizing Data: choosing the right chart
If you walk into a hardware store, you might see an entire aisle of screws—short ones, long ones, phillips head, flat head, ones with weird little anchors on the ends. They might all be screws, but they each serve a specific purpose—for wood or cement, for different screwdrivers, for thick or thin materials. It’s the same with data visualizations. They might all be charts, but pie charts, bar charts, and line charts all serve a different purpose. When data visualizers use the wrong one (often unintentionally), you’re left with a chart that doesn’t really make sense.  Below are charts using the...

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