PME-NA

Data Literacy for Conceptual Change: An Integrated Model With Special Applications in Climate Change Education

• In Event: Data Literacy for Conceptual Change: An Integrated Model With Special Applications in Climate Change Education

Description

The purpose of this theoretical paper is to synthesize evidence and theory at the intersection of data literacy and science education and proposes a model describing the role of data literacy in conceptual change: The Data Literacy for Conceptual Change (DLCC) model. The DLCC positions data literacy skills identified in the math education literature in terms of models of conceptual change. Notably, we elaborate on key critical data literacy skills that serve to help students make personal meaning of data, and account for the role of affective dimensions (e.g., motivation, emotion, and beliefs) that promote scientific conceptual change. Incorporating affective pedagogical goals from mathematics education, which emphasize the emotional dimensions of learning about issues of injustice, the DLCC model adapts such goals to support students’ emotional processing of data, with specific applications for climate change learning.

Authors

• Ian Thacker, University of Texas at San Antonio

• Imogen Rose Herrick, University of Kansas