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Elizabeth Bonawitz

Harvard University
Graduate School of Education

Associate Professor of Learning Sciences
Psychology Department
United States of America

PhD, Brain and Cognitive Sciences, Massachusetts Institute of Technology, 2009
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Research Focus
Elizabeth Bonawitz studies the Science of Learning. Her research bridges empirical work in cognitive development with computational models of learning. She uses experiments in the lab to study how children learn from observation, teachers, and their own interventions (play). The computational models help to explain why learning occurs in these different contexts, starting with the idea that the mind is a kind of computer that interprets information from experiences. An important part of this work is to characterize how learning mechanisms interact with different early childhood experiences. She hopes this research will connect to educational practice, particularly in underserved populations.

What have I achieved during my fellowship?
I am very grateful to Jacobs for the opportunity to build a strong network of collaborators and to expand my research program on children’s learning. Specifically, I have built out a strong empirical basis for the role of questions asked by a knowledgeable and helpful teacher in shaping children’s exploration, motivation, memory, and learning.  I have demonstrated how early experience with these questions varies and shapes subsequent inferences in early childhood. Jacobs has also supported new collaborations with fellows.  This includes ongoing close collaborations with Fellow Allyson Mackey with whom I am building out a research program bringing her expertise in neurological development of at-risk children to my research program of computational models of learning, to explore questions of curiosity-supporting behaviours and interventions in these populations.  I am also engaged in long-term collaborations with Fellow Garvin Brod, with whom we have two large projects in progress, exploring children’s scientific belief revision employing physiological measures (pupil dilation), cognitive measures (role of executive function and prior beliefs), computational models (Bayesian learning models), and empirical manipulations (predictions, explanations of outcomes). This work has been accepted for talks at upcoming international conferences and is in progress. I have ongoing paper collaborations with Fellow Hyowon Gweon exploring how children evaluate teachers, and have a collaboration with others recently applying for a large-scale grant to help build out large-scale sharable testing resources for the broader cognitive development field. Finally, I have an ongoing collaboration with Fellow Yee Lee Shing exploring the associations between school experiences and pedagogically cued exploratory play (as well as numerous additional measures of cognition and brain development through Yee Lee’s lab). I’m delighted for these connections, as they broaden my research program to be more impactful on our approach to the science of learning.

My plans for the future
The Jacobs Foundation has further inspired me to make more concrete connections between my basic science research and practice, so I am thrilled to move to Harvard Graduate School of Education where I will better be able to explore the implications of these basic science theoretical advances in practice and policy. I have also broadened my program to explore more concrete measures of curiosity, as encouraged by Jacobs Foundation, and am building out a program that includes EEG and neurological measures of active learning in development. Jacobs fellows have provided me with the foundations (and courage) to get involved in cognitive neuroscience and I am delighted to develop this aspect of my research program in future years.  I am also moving more toward thinking big picture about how to change broadly how developmental science research is conducted and shared. This includes building out new models of large-scale researcher collaborations (see Sheskin et al, TICS 2020) as well as thinking about broader recruitment of participants to make sure data collection is representative of world populations.

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