Simplifying Case Studies Using Data Points
One of the things I try to do before any semester is to be organized. My lesson plans, choice of case studies, laboratory experiences, and the different assignments I decide to use each semester are the result of extensive organizing, sequencing, and scheduling to take my students through the different topics we explore.
But the COVID-19 pandemic changed all of that. I don’t just mean in the beginning when we moved the course from in-person to online education. No, I am specifically referring to what came after that.
When I returned to class in Fall 2020, my course setups introduced new levels of volatility to what had always been a fairly predictable journey through topics in ecology and evolutionary biology. I taught online lecture sections for my large introductory undergraduate biology class for majors, as well as hybrid (both online and in-person) courses later in 2021. Previously, I had been able to use highly choreographed case studies and other active learning experiences that would sometimes cover multiple class sessions. Now, I had to adapt case study teaching to a new learning experience. The challenges were many, but not insurmountable.
The solution I arrived at for this particular predicament was to follow Thoreau’s advice from the book Walden and “simplify.”
I refused to sacrifice the quality of the learning experiences. But I knew that the extensive case studies that were the core of my teaching would not work as well in this new landscape. What I needed to do was take what worked from those case studies and modify it to fit in my new classroom.
After breaking down multiple case studies into their basic components to identify what made them successful, I found my solution. It’s all in the data. Data are what we want the students to work with in STEM classes. Data are what they will encounter in research. It’s the way case studies engage students with questions, hypotheses, and data that is their value.
Once I came to that realization, my path forward was clear. I needed to give students experience working with data, but I needed data experiences that were easier to engage with and begin exploring. I turned my attention to the BioInteractive Data Point resources and began combing through them to find resources that had the same focus, topics, and content as my case studies.
Data Points are incredibly useful resources because they get students into an experiment or topic quickly using figures from the primary literature and a guided set of supporting questions. Rather than requiring an extensive setup like standard case studies, only minimal introduction is required to teach with most Data Points. For example, a core concept in my course is phylogenetic tree data collection, analysis, and interpretation. I have a collection of case studies I have used over the years to teach tree thinking. But, for a variety of reasons, they don’t work as well in the virtual classroom.
For my new approach, one of the resources I chose to use is the “Evolution of Ant-Mimicking Beetles” Data Point. After lecture and laboratory sessions that introduce the basic steps and skills for phylogenetic tree thinking, I present the students with the Data Point at the beginning of a class session and ask them to work through the discussion questions in the “Educator Materials.” Students work in breakout rooms on Zoom to extract as much information as they can from the figure and questions.
Following 10 minutes or so of discussion, students return to the main Zoom room and post the information they gleaned from the Data Point in the chat. In most instances, they return with a fundamentally accurate interpretation of the general idea in the Data Point. Students typically identify the important variables and trends. After they briefly discuss and think about those items, I use their responses to pose additional questions about the genetic or evolutionary mechanisms driving this phenomenon, what ecological interactions are shaping this evolutionary story, or what questions the researchers were trying to answer. One of the most useful things I ask them to do is to figure out the researchers’ original hypothesis and how these data might support or fail to support it. I then send students back to the breakout rooms for further discussion. When they report back, their responses often indicate that they are thinking about not just what the figure shows but also what it means.
This approach seems to be working quite well. In my previous case studies, we constructed the story, and then I guided the discussion to a point where data could be analyzed and interpreted. This new approach reverses that. Students grapple with the data first, then construct the story that goes with it, giving the content in the figure meaning to them. There are the occasional grumbles and groans, but the overall response is positive. Students have commented that they like the way the Data Points make the science we talk about real and how they are starting to consider science as an effort to answer questions rather than a practice in memorizing facts.
That is the whole purpose behind a case study pedagogy: to let students experience the case and construct knowledge that has meaning for them. I am not saying that the other ways I have used case studies don’t work. This new method just takes another path to arrive at the same objective. Additionally, I have been happy with how the entire learning experience using these hybrid Data Point/mini case studies can be completed in a single class session. Furthermore, it is extremely simple to share these resources with students who miss a class session. Recreating the learning experience with more extensive case studies is simply not possible. However, with mini case studies using Data Points, that can be done. All that is required is sending the Data Point to the student as an electronic file (e.g., PDF) and providing a few guiding questions. While it doesn’t completely recreate the in-class experience, it does allow these students to go through the process of thinking about and even struggling a little with the data to construct their understanding of the material.
This experience and journey of the past 18 months has opened my eyes to a new perspective on how to structure classes. For the virtual world I currently teach in — and even into the future when I hopefully return to a physical classroom — the mini case studies are going to be a tool I turn to frequently in my teaching. The flexibility they offer and the new approach they bring to data exploration in a case-based pedagogy are something I had not previously appreciated about Data Point activities. But I fully embrace them now! I urge everyone to consider new ways they can bring these incredibly useful resources to their classroom.
I recently read a research paper that investigated the types of changes humans typically consider when they want to improve something or solve different types of problems. When participants in the study tried to resolve the challenges in a variety of experimental scenarios, they tended to make changes that added to the system and “systematically” overlooked changes that involved removing an existing component (Adams et al. 2021). The authors concluded that when humans try to “improve” an existing system, they frequently default to adding components, which often increases the complexity of the system and expense for the solution. Seldom do they consider subtractive changes to simplify the system, unless prompted to do so.
As I considered this research, I realized that this was similar to my case study and Data Point experience in many ways. For many semesters, I have found solutions to different challenges in the classroom by adding to what already existed. It wasn’t until I encountered the unique experience of converting a course that is traditionally an in-person experience to a virtual one that I began to consider simplification as a solution. By adapting Data Points as mini case studies, I am convinced that I have been able to simplify delivery of content without sacrificing the final quality of the learning experience.
Adams, G.S., Converse, B.A., Hales, A.H., et al. People systematically overlook subtractive changes. Nature 592, 258–261 (2021). https://doi.org/10.1038/s41586-021-03380-y
J. Phil Gibson is a professor of biology, microbiology, and plant biology at the University of Oklahoma. He doesn’t really do much these days except work on his podcast (BioTA), play disc golf, and think about gardening.
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