Learning Progressions and Trajectories from STEM to Data Science: A Systematic Review

• In Event: AERA Roundtable Session Thursday 2:15 pm
  In Roundtable Session: The Making of Minds: Pedagogies, Literacy, and Progressions in a Changing Curriculum

Abstract

As data becomes increasingly central to decision-making at all levels of the society, there is a growing call to integrate data science and data literacy into K–12 education. A key step in this process is developing validated learning progression frameworks to guide curriculum and assessment design. It is important to learn from established STEM education research on the development and validation of learning progressions and trajectories. This study systematically reviews literature published between 2011 and 2024 on STEM learning progressions and trajectories, aiming to provide guidance for researchers developing LP/Ts in data science and data literacy, as well as for those advancing LP/Ts in other STEM domains.

Authors

• Zhen Xu, University of Tennessee

• Cody C. Pritchard, University of Tennessee