PDI-8: We've Got Data! Using Mathematical Representations to Talk About, Model, and Explain Scientific Phenomena
Date: Wednesday, March 17, 2010
Location: Philadelphia Marriott Hotel, Room 406
Science Area: Integrated/General
Intended Audience: Elementary; Middle Level
Recommended Pathway Sessions
Presented by:
TERC
Presenters:
Sally Crissman, TERC
Sue Doubler, TERC
Framing Questions:
- How can grappling with data deepen students' scientific understanding?
- What are students' own ideas about representing data?
- What norms for creating and reading representations need to be explicitly taught?
- How can representations anchor scientific discussion and debate?
- How can data help students learn to reason critically and flexibly?
- How can what students are learning in mathematics and science complement each other?
Description:
The action of classroom science investigations often stops short once the data are collected and displayed, but before students get a chance to look for trends or patterns, discuss and debate the weight of evidence and robustness of explanations. It's as though the ingredients have been gathered but there’s no time to cook! If reasoning from and about data is such an important part of science learning, why is so little time devoted to it in the classroom? This workshop will provide strategies for making the most of opportunities to work with data in the service of deeper understanding of science concepts and scientists' ways of knowing.
In this institute, participants will work with scientific data sets they collect themselves and that have been collected by others, explore different ways to represent or display the data, and discuss which representations help us see or notice patterns or support an evidence-based argument. Participants will engage in scientific discussions anchored by data and reflect on the norms and skills that support classroom discourse.
The institute will also address practical questions such as
- How can I add a data literacy strand to an already crowded science curriculum?
- What data representations are most important for students' science learning?
- When teaching about data, is one curriculum sequence better than another?
- How do we help students leverage their work with data in mathematics in their science investigations?
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