This workshop builds data literacy for science instruction through mathematical modeling with data. In this session, co-facilitated by the NSTA Professional Learning Team and Tuva, participants will work in a student role, using data to make sense of phenomena as they explore how distributions describe variability using dot plots, box plots, and histograms, and when to use mean, median, or mode. They will also model relationships between variables using scatterplots, lines of best fit, and concepts such as correlation, association, and linear vs. nonlinear patterns. Participants will reflect on how these skills can be incorporated into their own classrooms.
TAKEAWAYS:
Participants will strengthen their understanding of distributions, variability, and relationships through mathematical modeling and will consider how to bring these ideas into their own classrooms to support student sensemaking with authentic science data.
SPEAKERS:
Jocelyn Foran, Brianna Reilly Oliveira