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As a principal investigator on a nearly $890,000 National Science Foundation grant, Bridget Mulvey, a ������Ƶ Associate Professor of Science Education in the College of Education and Human Services, is helping students see science as a living, dynamic way of making sense of the world.

Titled, “Separating the Signal from the Noise,” the project is a three‑year collaboration among ������Ƶ, the Concord Consortium, the University of Washington, and the Anchorage School District. Its ambitious goal is to empower Alaskan middle school students to investigate local natural and human‑caused seismic events using seismic data and machine learning techniques used by seismologists, or scientists who study Earth’s vibrations like earthquakes.

Mulvey also serves as the project’s research lead, guiding the scientific vision while also supporting the development of the machine learning curriculum module and teacher training. Her work ensures that students aren’t just learning about earthquakes—they’re learning to think and act like scientists and data analysts.

A Classroom Built on Shaky Ground

Because Anchorage is one of the most seismically active regions in the United States, the region experiences earthquakes, rockslides, avalanches, ocean waves, and even human activity—from concerts to construction— that send vibrations through the Earth’s crust. Students participating in the project will install scientific‑grade seismometers in their schools to collect real‑time data and use machine learning models to classify any seismic events they detect.

“When students use machine learning to analyze seismic data, they’re not just learning about earthquakes, they’re learning how to make sense of complex, real‑world datasets,” said Mulvey. “It gives them a way to see the Earth’s surface as an evolving system they can genuinely investigate. When we show them that the ground beneath them has a story to tell, we can also show them that they have the tools to listen and decipher it.”

Research Based in Scientific Concepts

Mulvey’s involvement is grounded in the project’s research goals, understanding how integrating computational practices into science classrooms affect students’ attitudes, scientific investigation skills, and their understanding of Earth science concepts.

“This seismic project is more than a curriculum, it’s a blueprint for how schools can integrate computer science, Earth science, and data literacy in ways that feel meaningful and connected to students,” Mulvey said. “By giving young people access to real seismic data and the tools to analyze it, this project helps them build scientific understanding and computational confidence.”