Data Literacy at the Leonard Gelfand STEM Center


Data Literacy at the Leonard Gelfand STEM Center

In an effort to understand how STEM practitioners around the country are engaging with data literacy in their space, we’re launching a series of interviews. First, I’m sitting down with Jim Bader, the Executive Director of the Leonard Gelfand STEM Center at Case Western Reserve University. 

We chat about exploring data literacy at a K-12 STEM outreach center, Jim offers some resources to other educators looking to incorporate more data literacy into their work, and we consider how data is not necessarily “good” or “bad” - it just is. As Jim says, “students often struggle with that kind of ambiguity.”

I hope you learn something from this interview - I certainly did! 


Sarah: How do you engage with data and data literacy in your work?

Jim: In our capacity as the K-12 STEM outreach arm for the Case School of Engineering and College of Arts and Sciences, we abide by the NSF mantra “In God we trust, everyone else bring data.”

In the same way, most would agree that reading and writing skills are necessary for virtually every occupation, we believe data literacy skills are just as important in the modern workforce. It is hard to imagine an occupation where fluency in data literacy is not required in some capacity. I challenge you to name an occupation that does not require some form of data literacy to be successful. Go ahead, I will wait.

As a result, we intentionally build data literacy into our programs by placing an emphasis on using quantitative approaches. Specifically, we place a heavy emphasis on measuring “stuff,” whatever that stuff may be. 

Sarah: Are there any programs or initiatives at your organization that you’d like to highlight, pertaining to data or data literacy? Why are they important?

Jim: On the environmental side, the Kelley’s Island Collaborative, Learning Streams International, and Environmental Heroes all are freshwater-driven programs that expose students to data they do not normally encounter in school settings. For instance, most students have some idea what pH is and they all can tell you if 120°F is hot or cold (don’t worry, we will all be using metric measures by 1979). However, talk about phosphate concentrations in Lake Erie or conductivity levels in the Cuyahoga River, and students are faced with unfamiliar units and no frame of reference as to what constitutes a high or low value. Another issue measures like this bring up is the idea of “good” and “bad”. For instance, let’s say students measure a conductivity value of 225 µS/cm. Assuming they can figure out the units (not usually), the first question they ask is that good or bad? Healthy or unhealthy? Sometimes, levels are neither good nor bad, they are what they are, and students often struggle with that kind of ambiguity. 

Another aspect of working with environmental data that I like is that of scale. Back to phosphate levels, it makes a big difference if the data is reported in mg/l or mg/ml or µg/l, so students are forces to struggle with units and issues of scale.

Sarah: Have you engaged educators in the above work? If not, are there other ways in which your organization engages educators?

Jim: We engage educators with data literacy in two ways. The first is directly when we are doing professional development. In those cases, we are often explicit in addressing data literacy challenges and have discussions about the merits of various approaches. The second is when we are working with their students. In those cases, we are directly addressing the issues with students, but we know teachers are listening and hope that some of what is discussed rubs off on them so they can incorporate these conversations with their next set of students.

Sarah: Are there partner organizations that you work with that we should know about?

Jim: Besides the usual suspects (schools), public libraries are tremendous partners and supporters of this kind of work. Perhaps because literacy, in general, is ingrained in the mission, libraries understand and appreciate the importance of all types of literacy, including data literacy. After all, these are institutions dedicated to cultivating an informed and literate citizenry, so it makes sense that data literacy is something they value as much as we do. 

Sarah: How might educators learn from your initiatives to enhance their own data literacy practices?

Jim: The simplest lesson educators can learn from our work is to always try to measure things and ask their students to do the same. Complement subjective qualitative measures with objective quantitative measures. Sometimes, this requires a fair bit of creativity, but that is the fun part. Engaging with data this way is one of the core Scientific and Engineering Practices espoused by the Next Generation Science Standards.

Sarah: Do you have any data literacy media to recommend? (e.g., blogs, podcasts, YouTube channels, etc.)

Jim: One excellent data literacy resource for K-12 educators is the HHMI BioInteractive website. This site has a new module specifically designed to walk students through various data interpretation scenarios using data from two popular BioInteractive lessons. The Data Explorer portal can be accessed at

I actually get a lot of really useful data literacy information and ideas off Twitter. STEM people like to tweet, so if you are following the right people, you can come across some really helpful information. The majority of people and organizations I follow professionally are related to freshwater in general and the Great Lakes specifically and I frequently come across creative ways to present data. 

There is also a data visualization group on Reddit (r/dataisbeautiful) that is a fun community to explore.

Sarah: What advice would you give someone looking to enhance their data literacy practices, in your field?

Jim: Read, read, read. The best way for me to learn is to learn from others and I do that by reading as many different technical reports as I can. That way, I learn from others who are far better versed in data literacy than I am.


A big thanks to Jim Bader and the Leonard Gelfand STEM Center for participating in this series!