Learning statistics through Ice Core Isotopes
Polar regions are particularly sensitive to climate change and play an important role in it. The richness and interdisciplinary nature of polar research suggests a potential to enhance student learning. To harness this potential, we developed Polar ENgagement through GUided INquiry (PENGUIN) modules, which use a computational tool to give a wide variety of students hands-on experience working with polar research.
Here we present a PENGUIN module in which students explore how isotope concentrations in polar ice cores can be used to reconstruct temperature over the last 800,000 years. We use a model-based inquiry framework in which students develop and refine a mental model, starting by learning about how temperature influences isotopic concentrations in Antarctic snow. Students think about how to quantify the temperature-isotope relationship, formulating hypotheses and questions. They then explore what kinds of data and analysis are needed. Using R Studio, students then collect, visualize, and perform linear regression on measurements of current Antarctic temperatures and isotope concentrations. They apply their results to derive a long-term record of temperature from an ice core. In small groups, students compare findings and conclusions, and come to a consensus about results. Finally, students present findings in a whole-class discussion. Additional topics include exploring CO2 vs temperature in the modern and ice core record, and discussing physical models and correlation vs. causation.
To test the efficacy of the module, we are developing a knowledge test, with the input of student perspective through focus groups. Deployment of the new module and knowledge test is planned to start in fall 2021, and is expected to lead to improvements in the module as well as improved understanding of how students learn. The resulting module will be disseminated via the PENGUIN page on the SERC website: https://serc.carleton.edu/penguin/index.html.