She holds a PhD in Learning Sciences from Northwestern University, and Bachelors degrees in Mathematics and Elementary Education from the University of San Diego. Michelle studies how expressive technologies (including computational modeling, graphical and narrative programming, and advanced data analyses and visualization) might provide middle and high school learners with bridges between their existing knowledge and experiences, descriptions of scientific phenomena, and the languages of mathematics and science. Michelle was elected 2012-2013 Chair of the American Educational Research Association's Special Interest Group in Advanced Technologies for Learning (SIG-ATL), and is PI of a new NSF Cyberlearning grant (with Brian Gravel) to develop and study student learning with SiMSAM, an integrated modeling, simulation and data analysis tool for middle school STEM students.