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Data Science Education Webinar (Lisa Hardy)

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Title: From Data Collectors to Data Producers: examining shifts in students’ relationships to sensor data

Description: In data science education, students will encounter and be asked to interpret large datasets that they did not create themselves — often with limited information about why or how these datasets were constructed. In contrast, studies of science practice highlight that the interpretation of data is strongly contingent on the methods by 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 presentation, Lisa Hardy will talk about ongoing research into students’ experiences using sensors and Dataflow software to produce their own data in the context of independent inquiry projects. She will discuss how the use of sensors can re-situate scientific data in the material world, and highlight its entanglement with students’ own decisions and actions. This can give students opportunities to call into question their own methods of producing data, and motivate the development of systematic practices of experimentation. We will discuss the implications of students’ experiences producing and interpreting their own datasets for their future encounters with data more broadly.

Bio:

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.

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