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Traci Higgins, Ph.D. is a Senior Research Associate on the Evaluating DMI project. Her work focuses on the development of measures of teaching and learning that can get beyond the surface level features of both. She has studied the impact of DMI on pedagogical content knowledge and mathematical knowledge for teaching in previous research and seeks to better understand how that knowledge translates into teaching practices that support learning for understanding. She was a member of the working group that produced “Using Statistics Effectively in Mathematics Education Research” and has co-authored book chapters, articles, and reports including a recent article in the Journal for Research in Mathematics Education describing research on the impact of DMI. Outside of work she can be found coaching youth sports, cooking, playing with her kids, and running her border collie-greyhound mix.

Sherry Soares

Sherry is the Project Coordinator for the Evaluating DMI project. Over the years, she has also worked for several projects in TERC's Adult Numeracy Center and Center for Earth and Space Science. She has a Masters degree in Applied Linguistics, with a concentration in English as a Second Language education, and is currently pursuing an Ed.M. in Curriculum and Teaching. She has also been an adult ESOL teacher for 14 years at various community-based programs, and she currently teaches at the Bridge to Learning and Literacy Program at Harvard University. She enjoys traveling, biking, and hanging out with her cranky old cat and three nephews.

If you have any questions about the DMI seminars or about this web page, please send her an email.

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Lindsay Demers

Lindsay Demers, Ph.D. is the Quantitative Analyst for the Evaluating DMI project. Her research interests are primarily methodological, with a specific focus on multivariate modeling and the application of hierarchical linear models to experimental data.  Prior to working at TERC, Lindsay worked as a methodology consultant at the University of Massachusetts’ Center for Research on Families. When she’s not analyzing data, she enjoys cooking, reading, and knitting.

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