Fostering Data Literacy in High School Science Classrooms: Learning and Instructional Challenges

• In Event: Data, Computation, and Science Education

Abstract

With the growing need for more data literate citizens in science and society, studies reveal the challenges students face when working with contextualized data, such as constructing claims from evidence and making inferences by considering context. In this study, we use a data literacy framework (Rubin, 2020) to examine how students interact with contextualized data, what challenges they face and how teacher instructions contribute to students’ development of data literacy. We analyzed student final reports, teacher surveys, classroom observation notes and teacher interviews from five high school science classrooms. Results show that most students demonstrated understanding of data context, but faced challenges in visualizing and reasoning with contextualized data depending on different instructional conditions.

Authors

• Jae-Un Yoo, University of Pennsylvania

• Jooeun Shim, University of Pennsylvania

• Noora Fatima Noushad, University of Pennsylvania

• Susan A. Yoon, University of Pennsylvania

• Amanda Cottone, University of Pennsylvania

• Katherine M Miller, University of Pennsylvania

• Michael V Gonzalez, University of Pennsylvania

• Ryan Urbanowicz, University of Pennsylvania

• Blanca Himes, University of Pennsylvania