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Research
We study how learners and teachers reason with data, computational models, visualizations, and digital tools.
Research areas →Computing • Research • Education
Learning with data, computing & science.
CoRE Lab brings together researchers, educators, and learners to investigate how computational tools, data, and scientific practices can support meaningful learning.
What we do
Our work explores the connections among computing, data, science, curriculum, and the people who use these tools in real learning environments.
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Curriculum
We develop learning experiences and practical materials that connect classroom goals with authentic data and scientific questions.
Teaching resources →03
Community
We collaborate with educators, researchers, schools, and communities to make learning more relevant and equitable.
Meet the team →Selected projects
CoRE Lab projects span data science education, computational modeling, climate learning, and critical digital literacies.
Writing Data Stories
Supporting learners in interpreting and communicating stories told through data, with attention to mathematical, scientific, personal, and social perspectives.
MoDa / Agent-Based Modeling
Exploring how students build, test, and refine computational models to reason about scientific mechanisms and real-world systems.
Rivulet
Tools and frameworks for helping educators find and customize pedagogically generative scientific datasets.
Computing as Multiliteracies
Investigating computing and digital practices as forms of literacy that can support richer participation in learning.
Resources
Explore classroom-ready materials and guides developed through CoRE Lab research and collaborations.
Latest news
Recent updates, presentations, publications, and work from the lab.
February 18, 2026
CoRE Lab at ISLS ’26
Sharing tools and findings from current projects at the 2026 Annual Meeting of the International Society for the Learning Sciences.
December 18, 2025
Choosy in Teaching Statistics
Strategies for making large datasets manageable while maintaining alignment with statistical learning goals.
July 31, 2025
Mapping Data Science Education Literature
A science-mapping analysis examining clusters in data science education research.
People
Researchers, students, educators, and collaborators contribute diverse perspectives to CoRE Lab projects.
Researchers & students
Explore current and former members, their research interests, and project connections.
Collaborators
Our work is strengthened through partnerships across education, computer science, science learning, and community organizations.