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A $600,000 grant from NSF is helping Melissa Zrada ’12 prep teachers to see data differently 

Melissa Zrada ’12

So much of the information we absorb in today’s world is visual — from maps to pie charts to dashboard icons. Being able to present data in a visual form, as well as being able to view and understand data, is fast becoming a necessary skill set across all professions, and it’s why Melissa Zrada ’12, assistant professor of integrative STEM education, is on a mission to improve data literacy for teachers.

She recently earned a $600,000 National Science Foundation grant to do just that, and will work in collaboration with another researcher, Michael Jabot from State University of New York–Fredonia on the project, A Data Visualization Experience for Preservice Teachers. Here, she answers a few questions about that work.

Why is data literacy so important to you?

Data is everywhere. We’re inundated on a daily basis. You can’t open a web page or the newspaper without seeing a big graphic or map.

According to Dataspire, a key voice in the field, data literacy is the ability to collect, organize, visualize, analyze, interpret, and share data for yourself and other people to use and understand. But research has shown us that not all teachers are confident in their own data skills, and this may impact how they teach about data in their classrooms. 

How will your project help?

The majority of teacher preparation programs do not explicitly teach data literacy skills or how to teach those skills. This project intends to provide higher education faculty with the tools to teach their students (pre-service teachers) how to integrate data skills into their future K–8 classrooms. We want to set teachers up for success in teaching these critical skills. 

Your work emphasizes not just understanding data, but how to present it in understandable ways too, is that correct? 

Yes. The project is focused on data literacy, and a big part of that for us is data visualization. Data visualization is any way to visually look at data. Oftentimes we think of the traditional graph types — bar graphs, line graphs, pie charts — but there are a multitude of ways that data can be shown and they are not all graphs, so we use the term visualization more broadly.

The goal is to get preservice teachers comfortable with these types of skills, so that when they go out into the field and are teaching certain concepts they think, ‘How can I get my students to visualize this data?’ or “How can I get them to understand this data?”

We want our youngest learners, our elementary school students, to be really comfortable with data by the time they get to high school and college.

— Kara Pothier MAT ’08


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