CO2 and pH in a System with Seasonal Upwelling: Using Large Oceanographic Datasets to Build Data Literacy Skills
I will first briefly discuss my experiences working with the Oceanographic Observatories Initiative to implement Data Labs into my classes and give an overview of the four OOI Ocean Data Labs that I have used. I will also introduce the survey method that I used to track student engagement with these activities. I will then do a brief walkthrough of the activity described above and the results from the student engagement survey. Lastly, I will discuss how these experiences have influenced my teaching in other classes and how I have applied the learning cycle approach introduced to me by OOI Ocean Data Labs to promote student metacognition. As part of my demonstration, I am happy to share all materials that I have developed for this and other relevant OOI Ocean Data Labs.
In this activity, students use online widgets to build connections across oceanographic disciplines – physics (upwelling, wind patterns), chemistry (dissolved gases, pH), and biology (photosynthesis, acidification impacts, fisheries). Each component of the learning cycle is explicitly considered. Students are invited to the topic using a podcast episode and an engaging visualization of annual CO2 patterns. They explore how atmospheric CO2 levels vary over long time scales (Mauna Loa Trends) and compare atmospheric CO2 levels to ocean CO2 levels off the coast of Oregon (OOI Ocean Data Labs). During the concept invention phase, students examine wind patterns throughout the year at this location (NANOOS Mapper). Students apply this new knowledge to describe the drivers of the seasonal CO2 and pH patterns off of Oregon (OOI Ocean Data Labs). To reflect on what students have learned, these concepts can be linked to fisheries and marine conservation in a class discussion. For example, though upwelling can lead to highly productive forage fish fisheries, it can also lead to reduced productivity of shellfish farms in the Pacific Northwest. Through this activity, students develop familiarity with various types of data visualizations, including regressions, time series data, and spatial data.
This activity is used in a 100-level oceanography class with students who are non-science majors. The activity takes approximately 45 minutes of class time, with students using their own laptops. I have also used portions of this activity in upper-level classes and can share both the 100-level and 300-level versions of the activity as part of my demo. I have used this in classes of 18-38 students, but I do not see any reason that it could not be used in a larger class, assuming that students have access to laptops.
Why It Works
This activity helps students to build connections across oceanographic disciplines. Furthermore, by providing students with the opportunity to examine various types of data/figures, this activity can help to build data literacy skills. Exploring data from large-scale observing systems (e.g., OOI Ocean Data Labs) gives students an appreciation for the abundance and diversity of oceanographic and atmospheric data collected globally and how far we've come in being able to better understand our world ocean. The widgets used in this activity are also aesthetically pleasing and interactive (you can choose specific time windows, click on points to see data values, etc.), which increases student engagement.