Guiding Student Exploration of Primary Productivity
Data Labs in the Classroom:
Teaching Tips from the Community
Dr. Jean Anastasia, OOI Data Lab Fellow 2020
I teach at Suffolk County Community College, a large, tri-campus community college on Long Island, that is part of the State University of New York system. I teach a 100-level Introduction to Oceanography course that is designed for non-science majors and was looking for a way to help students understand the process of science.
I wanted students to gain an appreciation that the results of science experiments and collected scientific data can be messy and that the real world does not perfectly conform to the idealized graphs and simplified trends that are presented in their textbooks.
I also wanted to develop exercises that could help students discover oceanographic concepts on their own rather than be told about them, in the hopes that this active learning would increase student success in understanding topics that are typically troublesome for students.
Those goals led me to my work with the OOI Data Lab project and the co-development of a new Data Lab, Factors Affecting Primary Productivity.
Learning Goals
Many students have a preconceived misconception that temperature is the most important factor controlling primary productivity in the ocean. The hope was that if students discovered for themselves how patterns of primary productivity correlate with nutrient levels and light levels and not with temperature, they would throw out their misconception and remember the important factors more easily.
Using real oceanographic data would also give them practice in uncovering important trends despite the variability of data and gain the experience of analyzing scientific data.
Implementation
As my course is an introductory class and the students, who are not science majors, tend to struggle with science and labs, I created a step-by-step lab handout that walked them through the data lab and asked questions along the way to help them discover what the data was showing.
We had already covered primary productivity in lecture, including how it is measured and variations in primary production across locations and seasons, and this preliminary background is important prior to completing the data lab.
Due to the COVID-19 pandemic, I implemented this lab in an online, asynchronous remote environment in the spring 2020, in a class of 48 students, and again in the fall 2020, in a class of 15 students.
Student Experience and Results
Based on student survey responses, the overwhelming majority of students enjoyed the data lab and felt that it helped them to learn the important concepts surrounding primary productivity.
Students did struggle to see larger scale trends due to the variability of the data. To help them with this, I posted a screen shot of one graph (showing light levels) in which I drew a smoothed line to help them visualize the larger seasonal trend and see past the day-to-day variability.
I assessed the effectiveness of the data lab in improving student learning by comparing prelab quiz questions with post-lab quiz and lab exam questions.
Overall, student understanding of the factors that affect primary productivity did improve with many students learning the importance of nutrients and light levels. However, some students stubbornly still held to the misconception of the large importance of temperature. Our work as educators is never done.
Teaching Tips
My main advice to instructors that want to implement this data lab in their classroom is to know your audience and provide an appropriate level of guidance. My non-science major, freshman and sophomore level students needed a fair amount of guidance, in the form of handouts, background lectures, and some help in visualizing trends, in order to achieve the learning outcomes of using the data lab. Upperclassman or oceanography majors would need much less.
I would also recommend, when the world allows, having students work in groups and in-person during class on these data labs. Although these online data labs can be used as remote labs and be done individually by students at home, the remote asynchronous format poses challenges. Students discover the trends in the data better when they work with their classmates and can bounce ideas off each other and have their instructor present to intervene and guide them when needed. I saw this when I implemented a different data lab while we were still in face-to-face classes in early 2020.
Download this 15-minute video in which Jean walks you through this Data Exploration and shares her teaching tips.
