Science Education to the Rescue? Assessing The Relationship Between Scientific Literacy and Carbon Emissions

Schmidt, A. (2022). Science Education to the Rescue? Assessing The Relationship Between Scientific Literacy and Carbon Emissions. [Doctoral dissertation, University of Tennessee, Knoxville].

This is a summary of my PhD dissertation. Use the links above to view the code and read the manuscript.

Human activities have radically changed the climate, negatively impacting all life on earth. The technical means to address this climate crisis exist, but there are major social and political hurdles that stand in the way. Education has been touted as one possible means for helping to move forward necessary action on climate change. A hybrid model of planned behavior and human capital helps explain how education can affect climate change. The current dissertation sought to assess what relationship may exist between changes in per capita carbon emissions and science education as measured by the Programme for International Student Achievement (PISA).

Results from multilevel growth models showed that countries with higher scientific literacy scores are significantly associated with higher CO2 per capita, though this is likely driven by economics and not directly by education. There were no significant relationships between changes in scientific literacy within a country and changes in that country’s emissions. This suggests evidence for the effect of science education is undetermined.

Based on this research, it is suggested that shifts in educational policies and practices that emphasizes and integrates science and climate change education across the curricula may have a greater effect on emissions. In addition, science and climate education should be imbued with a focus on effective climate change actions that can foster the individual and systemic changes needed to avert a global catastrophe.

Anthony Schmidt
Data Scientist

My research interests include data science and education. I focus on statistics, research methods, data visualization, and machine learning.