Using courses as vehicles to develop long-term time series data for student research

Undergraduate courses that emphasize field research skills and data literacy practices help prepare students for a variety of entry-level careers in the geosciences. Courses that are offered annually, or more frequently, are excellent platforms to develop local long-term time series of student generated data through repeated sampling. A course-based time series enables students to gain experience collecting their own data in the field, understand their data in the context of historical patterns, and gain access to larger data sets to conduct more sophisticated analyses. We present examples from an annually offered upper-level undergraduate marine biology field course where students contribute to and use long-term time series to build skills in multiple research training modules. To investigate intertidal community structure over time, students conduct established transects to contribute to a 40-year data set. To evaluate tidal effects on oceanographic patterns, students deploy a CTD over a tidal cycle to contribute to a multi-year observing effort in San Juan Channel, WA. In these example modules, students conduct a short research project where they use the course time series to test a hypothesis of their own development. This structure facilitates regular environmental monitoring through accessible course-based research, enables students to take ownership over a local data set and provides opportunities for students to build and develop critical data literacy skills. This model can also be adapted for courses at various levels and disciplines.

Presentation Preference: Either

Primary Presenter: Sasha Seroy, University of Washington (sseroy@uw.edu)

Authors:

Sasha Seroy, University of Washington  (sseroy@uw.edu)

José Guzmán, University of Washington  (jmguzman@uw.edu)