Open AccessAn Empirically-Based Conditional Learning Progression for Climate Change
Author(s) -
Wayne Breslyn,
Andrea Drewes,
J. Randy McGinnis,
Emily Hestness,
Chrystalla Mouza
Publication year - 2017
Publication title -
science education international
Language(s) - English
Resource type - Journals
eISSN - 2077-2327
pISSN - 1450-104X
DOI - 10.33828/sei.v28.i3.5
Subject(s) - climate change , conceptual change , exploratory research , set (abstract data type) , adaptation (eye) , psychology , path analysis (statistics) , mathematics education , sociology , computer science , ecology , social science , neuroscience , machine learning , biology , programming language
Climate change encompasses a broad and complex set of concepts that is often challenging for students and educators. Using a learning progressions conceptual framework, we develop a description of student learning of climate change based on our research findings and an extensive review of the science education research literature. In this exploratory study we present findings from written assessments (N=294) and in-depth interviews (n=27) with middle school students in which we examine their understanding of the role of human activity, mechanism, impacts, and adaptation and mitigation of climate change. Findings, along with evidence from the science education research literature, are synthesized into a first step empirically supported learning progression describing a path from an initial to a developed understanding of climate change. The empirically supported learning progression contributes to the climate change education research literature and provides the education community with a robust description of how student understanding of climate change advances over time.