I study how young people learn with and about computational representations – things like computer simulations, data visualizations, or interactive graphics. Rather than asking whether or how technology might be used to improve education, I take it as given that it is an important part of many people’s professional and everyday lives. People use simulations, visualizations, and analysis tools to conduct scientific and social investigations, to communicate about contemporary socioscientific issues, and even to tell stories in popular media. My research explores how youth learn to make sense and make use of these tools, and how to support such sensemaking through the design of software, curricula, and teacher professional development. I am especially interested in finding ways to give learners experience with computational representations in ways that are tightly connected to, and therefore feasible within, the existing K-12 curriculum. Here are some examples:


A major goal of this work is to enable youth to see themselves as authors of ideas, capable of judging the validity of scientific and data-based arguments and contributing to the scientific enterprise if they choose. Therefore I design tools that start by allowing youth to share their ideas about scientific phenomena in ways they are already likely to know well: things like sketching, storytelling, or flip book animation. They can then augment or overlay these constructions with programmed rules that allow them to see their creations “come to life” as computational representations, and to be critiqued, tested, and revised as scientific theories through reasoned argument and evidence.

I am a participatory design-based researcher, which means I consult with teachers, learners, and after-school professionals at every stage of design to make sure the tools we create are usable, and the theories we create really help us understand and improve how people teach and learn. While my focus is on youth learning, some of my research also explores how teachers make sense of computational representations as both a scientific and pedagogical tool.

I joined the faculty of the University of California, Berkeley Graduate School of Education in January 2016. I lead the Computational Representations in Education (CoRE) research group, and teach classes in science education and educational research. Before moving to Berkeley I was an Assistant Professor in the Department of Education at Tufts University from 2011-2015. My work has been featured in both general purpose and science/math education research journals including The Journal of the Learning SciencesScience EducationEducational Studies in MathematicsEducational Technology Research and Development, and the Journal of Science Teacher Education. I have served as the Chair and Co-Chair of the American Educational Research Association’s Special Interest Group in Advanced Technologies for Learning, and in 2014 I was honored to receive a National Science Foundation Early CAREER Award to pursue research on young learners’ data visualization competencies.