Ocean Tracks-College Edition: Asking Hard Questions to Benefit Students

A scientist, a teacher, and a data analyst walk into a room…

This describes the start of 4 days of intense discussion about the Ocean Tracks-College Edition (OT-CE) modules. Early in May, ODI’s Ocean Tracks curriculum development team met with faculty, like myself, who had used the OT-CE materials in their classrooms. I teach biology at Portland Community College and joined the workshop after testing three of the modules with my students. Since it was still raining in Oregon, it was lovely to meet at the Scripps Institution of Oceanography in California, in a conference room with a sunny view of the Pacific Ocean. Exploring Scripps, with a visit to the Birch aquarium and the Pelagic Invertebrate collection, had my geeky-biologist’s heart beating faster, reminding me why I care so much about impactful marine science education. What happens when you bring together PhD scientists, experts in informal education and curriculum evaluation, data analysts and faculty from vastly different institutions? They ask hard questions about curriculum!

After over 20 years of teaching, I have plenty of opinions about curriculum. But to do the best for my students, I know I need to go beyond classroom anecdotes and engage in scientific teaching (using “active learning strategies to engage students in the process of science and teaching methods that have been systematically tested and shown to reach diverse students). The same rigor I would apply to an experiment in the field needs to be applied in my classroom. One of the things that impressed me about Ocean Tracks was the intentionality behind the modules and the interface, informed by the research captured in the Visualizing Oceans of Data: Educational Interface Design guide.

It was great to see the Ocean Tracks team in action, and be able join in a discussion on a module focused on the physiology of highly migratory ocean predators with someone with a PhD in Deep-Sea Physiology AND someone else who could reference Vygotsky’s learning theories.  A lively discussion with the math/data analysis resource person reminded me that it is easy to be distracted by a beloved piece of content but sometimes you must let it go if it does not serve the curriculum objective. There is always a place for sharing the love we have for our disciplines (doesn’t everyone need to know about the diving reflex in marine mammals?), but if I am going to serve my students I need to focus on the learning objectives. If the objectives are fuzzy, the learning for the students may be fuzzy as well. The process of choosing or developing curriculum for a class often centers on the ‘what’. What content do I need to cover? The details are often driven by the level of the class, the need to fit into a sequence, and course- and program-level outcomes.  However, calls for reform in undergraduate biology education recognize that the explosion in content and the attempt to ‘cover’ the material is not serving students well. A focus on developing critical thinking skills through inquiry-based learning has helped shift the question of ‘what’ to ‘how.’ How do we help students develop the data literacy skills they will need for careers in STEM fields or even for navigating a world awash in information? The recognition that classrooms must be inclusive and serve individuals with a diverse set of experiences begs the question: how do those materials need to be presented to support a good learning environment? These are multi-disciplinary questions that often go beyond the specific expertise of any one faculty member.

 I decided to explore the Ocean Tracks curriculum with my students after hearing about it at an Ocean Sciences meeting in New Orleans.  The focus of the modules on building data literacy skills through guided inquiry with authentic data sounded good. But the promise of a user-friendly tool to introduce students to big data really made this worth investigating further, so I added three modules to my Fall course.

One of the Ocean Tracks modules my students worked through was Fact or Artifact: Interpreting patterns in Ocean Tracks Data. Like the title suggests, this was a module focused on helping students think about how data are collected and how that affects interpretation. For example the line between the tracking points may suggest the shark traveled across land, but does that make sense? Okay, so even if a student did decide that this must represent some kind of cool, land adapted shark (Sharknado anyone? Maybe a Sharkelope?), the structure of the module encouraged the student to consider what additional data would or would not support their conclusions. In the Ocean Tracks modules the animals are real, the data are real, and so are the complexities encountered.

Beginning students struggle with the idea of evidence-based arguments. Ocean Tracks modules are designed to give students opportunities to ask their own questions and to explore the data to answer those questions. Sometimes students struggled, but the activities are layered so multiple points of access helped them build confidence. Learning the interface took them more time than they expected but sometimes they spent more time because the Ocean Tracks library and data sets piqued their curiosity. The interface was user-friendly enough for students to complete some of the modules on their own when a series of snow storms shut us down for weeks at the end of the term. This is not a method of testing curriculum I would recommend, by the way, but it did allow me to see what the students were able to do on their own and highlighted where they needed additional support.  I plan to use Ocean Tracks with my marine biology class in the fall.

Student work is a powerful form of feedback and the experience of reviewing the modules in the company of people with very diverse areas of expertise was a powerful catalyst for reflection. The people that gathered for the workshop in May arrived with different perspectives but the scientist, the teacher, and the data analyst all agreed that helping students develop data literacy skills is critical for the future.  

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