From Data Collectors to Data Producers: Shifting students’ relationship to data

Colloquium | January 28 | 4-5:30 p.m. | Berkeley Way West, Room 1215 (2121 Berkeley Way, Berkeley, CA 94704)

 Dr. Lisa Hardy, Concord Consortium

 Graduate School of Education

Outside of school, students will encounter and be asked to interpret data and data representations that they did not create themselves — often with limited information about why or how these data were constructed in the first place. In contrast, studies of science practice highlight that the interpretation of data is strongly contingent on the context in which that data was produced. Data can never be interpreted straightforwardly, without careful consideration of the methods and instruments used to produce it.

In this talk, Lisa Hardy will discuss the ways in which data should be seen as actively produced rather than passively collected — and what design implications this view has for students’ engagements with data in science classrooms. She will present ongoing research into students’ experiences using sensors and Dataflow software to produce their own data in the context of inquiry activities in high-school Biology. From the lens of data production, we will discuss the implications of students’ experiences producing and interpreting their own datasets for their future encounters with data more broadly.

About the speaker. Lisa is a research associate interested in fundamental research in technology-enhanced STEM learning, as well as in designing and developing technology-based learning environments for K-12 and undergraduate STEM classrooms. Her dissertation research was in how university physics students develop scientific understandings when interacting with one another around networked simulations.

Her research aims to engage students in doing authentic science, reasoning with scientific models, and reasoning about the relationship between models, instrumentation, and data. Lisa is working on the InSPECT project to understand opportunities for embedding computational thinking practices within authentic science inquiry supported by “Maker” technologies such as Raspberry Pis and “Internet of Things” sensors.

Lisa has a double B.S. in Physics and Biochemistry/Molecular Biology from the University of California at Davis and an M.S. in Physics from the University of Wisconsin. She recently completed her Ph.D. in Education at UC Davis.

 goldwasser@berkeley.edu