University students in science and engineering are increasingly aware of the importance of the need to have data visualization and communication skills. Regardless of their future career choices, they understand that data skills are key.
However, few STEM majors include data visualization in their curricula. Higher education typically only offers students seminars on how to design a good research poster and students are, for the most part, left to learn data visualization skills on their own.
Graduate students who generate their own data also tend to perform more advanced data analysis and have complex stories to tell with their data. Often, they are working with datasets that hold many dimensions, lots of nuance, or uncertainty. Learning about data visualization at that level is as much about design as it is about science communication: distilling the key messages of one’s research and making difficult decisions about what content should be sacrificed at the altar of good design and a clear message.
Antonia Hadjimichael, assistant professor of geosciences, sought to address that need. She developed the Data Viz for Scientists and Engineers course, designed to provide undergraduate and graduate students in the college with a design and communication foundation.
“Personally, data visualization and visual communication in general has become increasingly important in my work,” Hadjimichael said. “I study climate impacts on water resources and planning for the future, which often requires the exploration of large simulation modeling experiments and large datasets with many dimensions. This has pushed me to be more inventive and thoughtful with how I communicate my scientific results. I have seen direct benefits from becoming a better visual communicator in my conference posters or talks. These are skills I want my own graduate students to pick up, but also, as an educator, I felt it important that new crops of students get some formal training on this.”
Hadjimichael spent more than a year conceptualizing this class and taught it for the first time during the spring 2023 semester.
“My vision from the beginning was to teach all I would want someone else to teach me when I was in college,” Hadjimichael said. “Some of it was very fundamental to design in general, like use of color and how some color scales match different types of data better than others. Some of it was very practical to what STEM jobs entail—in academia or industry. For example, how to save Python figures into scalable vector images instead of raster images, or how to guide your audience through a complex graphic using animations and annotations in PowerPoint. Some of it was just about getting them to be visually creative, even if we don’t know how to get there yet with coding or software skills.”
The students who took the course were in the physical sciences and most had no prior background on design or aesthetics, nor did they have advanced web coding skills, but they wanted to learn just enough to be better visual communicators.
“While my students’ backgrounds made planning the course more challenging, it kept the course focused on just the key skills that are most directly useful to scientists and engineers: coding simple analysis and charts in Python and creating more complex visualizations and infographics in Adobe Illustrator.” Hadjimichael said. “The goal was to stretch them a little on Python and also introduce them to some practical aspects of using software like Illustrator.”
Another dimension that strongly shaped the class was constructive criticism and feedback during the process of making the visuals, emphasizing growth more than strictly defined “correctness”.
“In most STEM education, students deliver an assignment and receive back a grade, with some instructor comments on what was wrong,” Hadjimichael said. “There’s little space for exploring weird ideas or being creative in a way that’s not formulaic. So, I wanted to emphasize a growth mindset and give the students a space to explore and try out design ideas in a low-stake environment before they submitted their final project.”
This process turned the classroom into a learning community where every student came to understand that the creative process is messy and iterative—and it is through this iteration that we learn from our audience about what works.
“Even though the final products were graded on having applied design principles from the class, all other homework was assessed on the basis of showing growth instead of perfection,” Hadjimichael said. “For example, demonstrating how they used feedback and on the quality of feedback they gave their peers.”
Hadjimichael said this classroom environment was a great introduction to real-life situations, where data visualization practitioners lean on a supportive community as they practice and refine their skills.
“From conversations with the students, they saw the feedback element of this class as essential to their growth and success,” Hadjimichael said. “When reflecting on this experience, this course design approach allowed for deeper and more meaningful learning, through building a sense of community and belonging. I loved how open and comfortable students were to express their thoughts, even if critical, about the designs and how they appreciated the importance of self-improvement and helping others.
Article is an excerpt taken from an article written by Antonia Hadjimichael and published in Nightingale Magazine, the journal of the Data Visualization Society. https://nightingaledvs.com/weaving-data-viz-into-science-and-engineering-education/