Li Ke

Environmental issues like wildfires can serve as effective science learning contexts to promote scientific literacy and citizenship. This project will partner with teachers, teacher educators, and disciplinary experts in data science, fire ecology, public health, and environmental communication to co-design a data-driven, justice-oriented, and issue-based unit on wildfires. In the unit, student will engage in various data practices to gain insights into the issue of wildfires and how it affects their lives and communities. The project seeks to theorize how learners can leverage disciplinary knowledge and practices in environmental and data science as a foundation for making data-informed actions towards a more just and sustainable society.

The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models. This project will address the gap by studying student learning with different types of models and will use these findings to develop and study new curriculum materials that incorporate multiple models for teaching about viral epidemics in high school biology classes.

This research project will produce curricular materials designed to help students learn about viral epidemics as both a scientific and social issue. It will engage students in scientific modeling of the epidemic and in critical analyses of media and public health information about the virus. This approach helps students connect their classroom learning experiences with their lives beyond school, a key characteristic of science literacy.