Tracking COVID-19 in the United States
Daily Do Playlist
Daily Do Playlist
Daily Do Playlists are suggested instructional sequences of two or more Daily Do lessons in which students coherently build science ideas over time. While each Daily Do lesson in the Playlist can be taught as a stand-alone task, guidance is provided for teachers to navigate students from one lesson to the next in the context of a We culture:
To better support both teachers and students, the individual Daily Do lessons in the Playlist have been updated to include tailored Google Docs, Slides, and/or Jamboard templates to facilitate students’ science learning in the classroom or virtual learning environment (synchronous and asynchronous).
In this first playlist lesson, students experience the phenomenon of the spread of COVID-19 varying among U.S. counties and use computer simulations (mathematical models) to begin to make sense of the patterns in the spread of COVID-19 they observe. Students apply their new understandings to make recommendations for their school to keep themselves, their families, and their community safe.
In the second lesson on the playlist, students observe the phenomenon of differences in the number of COVID-19 cases and deaths by race and ethnicity in their state and in others. Students engage in science and engineering practices to explain these differences, then propose justice-centered solutions for addressing the disproportionate impact of COVID-19.
In the third playlist lesson, students identify and explain the causes of the disproportionate impact of COVID-19 on racial and ethnic minority groups. Then they consider why the CDC guidance for how to slow the spread of COVID-19 is necessary but insufficient to address the causes that have led to the disproportionate impact of COVID-19. Finally, they propose system-level solutions for addressing the disproportionate impact of COVID-19.
The Daily Do Playlist: Understanding COVID-19 Disparities Using Computational Modeling is an instructional sequence in which students build toward using a computational model to design solutions to the disproportionate impact of COVID-19 on racial and ethnic minority groups.