Eric Kuo

ericEric is a postdoc interested in understanding cognition and its implications for how we teach science.  His research looks at how students learn and think about physics, focusing in particular around issues related to quantitative problem solving and students’ notions of what it means to learn physics.  Eric received his Ph.D. in Physics Education from the University of Maryland, before which he was, ever so briefly, a high school physics teacher.   He is now an assistant professor in physics at University of Illinois.  Eric’s website.



Natasha Holmes

NatashaNatasha is a postdoc studying learning and teaching in undergraduate physics labs. She evaluates learning outcomes within a learning context, such that her research is closely tied to course transformation. She has recently been designing and evaluating lab courses aimed at developing students’ critical thinking and experimentation skills. She is currently looking into the transferability of this lab framework to other settings, exploring the relationship between learning in lab courses and undergraduate research, and developing a closed-response test instrument to assess critical thinking for physics lab courses.  Natasha is now an assistant professor in physics at Cornell University.  Natasha’s CV and website.


Michael Flynn

Michael’s research focuses on the development and assessment of expertise in mechanical engineering design. He teaches courses in mechanical engineering (ME181 and ME324). He received his PhD in Mechanical Engineering and Masters in Education from Stanford University.








Engin Bumbacher

Under the guidance of Professor Carl Wieman, Engin Bumbacher has studied pedagogical and technological approaches for supporting critical, evidence-based reasoning in K-12 science education. In a series of laboratory and classroom studies, he examined what factors influence how students reason with empirical data about scientific models. He further developed and implemented a new web-based technology for enabling life science middle school students to engage in evidence-based reasoning. This technology integrates affordances for experimentation (with remotely accessible microscopes), data analysis, and computational modeling (with a block-based programing editor) into a single cloud-based web application for scientific inquiry. He holds a PhD in Learning Sciences and Technology Design from Stanford University, a MSc in Neural System and Computation and a BSc in Physics from Swiss Federal Institute of Technology Zurich.  See his research page here.