Can a data literacy program make science more accessible?

This story originally appeared on the MSU College of Natural Sciences website and is republished with permission.

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A data literacy program that is also changing students' relationships with science and scientists is entering its third round of funding with a new $1.5 million grant from the National Science Foundation.

In collaboration with Auburn University, the Kellogg Biological Station, or KBS, Data Nuggets program will work to identify factors that improve equity and success in undergraduate STEM education.

Data Nuggets, launched by Michigan State University in 2011, is a curriculum development project designed to help students better understand and use data. The program showcases how science, technology, engineering, and math professionals actually work with data by sharing their stories, which also allows students to relate on a much more personal level.

Data Nuggets challenges students from kindergarten through college levels to answer scientific questions using data to support their claims. The questions and data originate from real research provided by scientists whose studies range from physics to ecology to animal behavior.

To add the personal element, Data Nuggets is collaborating with Project Biodiversify (another educational program started at MSU) to add scientists’ biographies, which include information like their hobbies and lives outside of science. This helps students relate to the researchers and see them less as strangers in lab coats and more as scientific role models.

“We have found that it is the scientists who engage the students in the activities,” he said. Elizabeth Schultheisco-director of the Data Nuggets program. “If they connect with the role model, then you can get students to do the data literacy activities because they know, ‘Oh, this is a real person. I relate to this person. And I’m working with real, authentic data. I’m not just doing useless work.’”

Schultheis, who earned her PhD in plant biology at Michigan State University, is also the education and outreach coordinator for KBS’s Long-Term Ecological Research (LTER) program, which supports Data Nuggets. Schultheis and co-director Melissa Kjelvik developed and led the program, and formed partnerships to research and fund it.

“With our current research, we're trying to figure out what it is that's special about students that really resonates in terms of role models,” Kjelvik said.

“Our research will investigate how and why role models are critically important to students,” said Cissy Ballen. Ballen is an adjunct professor in Auburn’s Department of Biological Sciences, the lead institution on the NSF grant, which builds on Data Nuggets’ past success and will help ensure its future impact.

“The theory behind this is that students need to be able to see a scientist’s success as attainable in order to identify with it,” Ballen said. “My prediction is that students will find success most relatable when they see that some scientists, like themselves, have struggled with science but were then able to overcome it.”

Making data speak

Many students get tears in their eyes when they hear terms like “data” or “science.”

Even Schultheis admits that he didn't appreciate the importance of data until he was a graduate student collecting it on his own. The problem, he said, is that children are often taught how to make a graph, for example, but not how to make it. because.

“I never really learned to care until I understood that the reason I make a graph is because I want to answer a question,” Schultheis explained. “I need to see the data, what it looks like. And that’s why I make a graph.”

Data Nuggets doesn’t change the skills taught in conventional curricula. Students still learn how to make and label axes, for example, and then how to plot data to create charts. But they also get a more immersive introduction to why real people use these skills.

“Our goal with these Data Nuggets modules is that everything is always in real context and always in service of a scientific question,” Schultheis said. “It’s always: Here’s a scientist. This is the question that really concerns him and the reason he collected this data is because he wants to answer this question. And you create the chart to visualize it so that you can see what the data is telling you.”

Data Nugget activities come in four levels, so instructors can use the ones that best fit their specific classes. Level 4 activities are designed for high school and college students, while Level 1 activities are appropriate for elementary and upper grades looking for a refresher after summer break, for example.

Instructors also have flexibility in how to present an activity based on their goals. For example, instructors can choose activities with rich graphics so that students can focus on interpreting what they see to answer questions.

Or students can be given blank grids to gain experience creating useful data representations from scratch.

Connie High, a science teacher at Delton Kellogg Middle School, about five miles from KBS, calls Data Nuggets “a game changer.”

She said her students, when new to Data Nuggets, can usually make claims and find evidence to support them. The challenge is learning to articulate the connection between the two.

“They really struggle to connect claims, evidence and reasoning. They tend to repeat evidence over and over again,” High said.

“With Data Nuggets, we definitely see an improvement from the beginning of the year to the end.”

Humanizing data

The Data Nuggets program began 13 years ago as a grassroots collaboration between KBS researchers (including Schultheis and Kjelvik, who were then graduate students at KBS) and K-12 teachers, including High School.

Since then, more than 120 scientists have contributed to over 120 data literacy activities. Tens of thousands of people regularly use the Data Nuggets website. Links to various Data Nuggets stories can even be found in science textbooks.

“Building long-term relationships is why we got such good insight from educators into what their students needed — because they already trusted us and we went into their classrooms and learned from them,” Schultheis said. “And building relationships with scientists who trust us to tell their stories correctly, who are giving their own stories for students to read and learn, remains critical to our success.”

But how best to present and present data is up to Schultheis and his colleagues. Previous research has supported the idea that it's essential to focus on the scientist and why they collected the data. After all, data is just numbers. It's human interaction that puts the numbers into perspective, gives context to the scientific question, and gets students engaged in the activity.

“Humanizing data is at the heart of this work,” Ballen said. “Data Nuggets is such a successful resource because of the way they humanize the data component and contextualize it within the science itself and show that it’s being done by scientists you can relate to. They do that very well.”

With its third round of NSF funding, Data Nuggets is attempting to refine how best to present scientists’ role models and stories to further enhance student engagement with science.

The goal is not only to increase the representation of underrepresented groups among contributing scientists, but also for students to see that they share some things in common with the scientists they see.

“We used to ask students to draw what a scientist looks like and they all drew someone who looked like Albert Einstein,” High said. “It’s incredibly important for them to see that there are scientists who look like them.”

“You can imagine that if you were a student sitting in a classroom, you might be given an activity that featured a scientist from a prestigious university with awards and that sort of thing, and that might not be very relatable,” Ballen said. “Success might not be perceived as something attainable.”

Data Nuggets is working to combat that perception.

For example, there’s a Data Nugget called “Trees and the City,” which features a photo of a smiling University of Minnesota ecologist named Adrienne Keller wearing a bike helmet and sunglasses. A video shows Keller biking through Twin Cities neighborhoods as she describes her interest in tree patterns. She poses the main question of her dataset: “Are there differences in total canopy cover or the number of tree species planted in a neighborhood based on residents’ income level or percentage of BIPOC (Black, Indigenous, and People of Color) residents?”

Another Data Nugget article was written by a community scientist from Bayfield, Wisconsin, located on the south shore of Lake Superior. He is pictured wearing shorts and sneakers while standing on the ice.

For her discovery, she used historical data to answer her question of whether winters were getting shorter and changing the dynamics of how people could travel in the area.

It turned out that he was also a high school student.

“That’s the dream outcome,” Schultheis said, “that students realize how powerful data is and can be advocates for themselves and their communities because they can really go to the source of information and ask and answer questions.”