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Teaching Data Viz and Communication as an Undergraduate Biology Course: Assignments and Projects

Author(s): Kristine Grayson1, Angie Hilliker1

University of Richmond

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The increasing production of data necessitates that students develop skills in data exploration and visualization, especially of large data sets. While a wide variety of resources have been developed to facilitate the use of authentic data in the classroom, many biology courses lack the time for students to develop the data science skills needed to wrangle complex datasets.

We used concepts and examples from Fundamentals of Data Visualization (Claus Wilke) and Calling Bullshit (Carl Bergstrom and Jevin West) to teach students how to create truthful, beautiful data visualizations and recognize common pitfalls. Students learned data visualization principles through examples from both the media and science publications. Throughout the course, we emphasized issues of scientific ethics, refuting misinformation, data dredging, and equity in data collection and usage. 

The second half of the course focused on demystifying programming logic and syntax to show biology students how programming allows easier processing of large datasets, gives flexibility in visualization choice, and produces reproducible workflows.

Materials provided:

Dear Data Assignment

TidyTuesday Assignment

Midsemester Project (using datasets from Our World in Data)

Final Project (using publicly sourced datasets)

Please see for our syllabus and course resources. All materials were equally co-developed by Angie Hilliker and Kristine Grayson (University of Richmond) and taught for the first time Spring 2021 in a hybrid course with 17 students in person and 1 remote student.

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