Incorporating Computer Programming & Data Science into a Guided Inquiry-Based Undergraduate Ecology Lab

Abstract

The biological sciences are becoming increasingly reliant on computer science and associated technologies to quickly and efficiently analyze and interpret complex data sets. Introducing students to data analysis techniques is a critical part of their development as well-rounded, scientifically literate citizens. As part of a collaborative effort between the Biology and Computer Science departments at William & Mary, we sought to develop laboratory exercises that would introduce basic ideas of data analysis while also exposing students to Python, a commonly used computer programming language. We accomplished this by developing exercises within the interactive Jupyter Notebook platform, an open-source application that allows Python code to be written and executed as discrete blocks in real time. Students used the developed Jupyter Notebook to analyze data collected as part of a multiweek ecology field experiment aimed at determining the effect of white-tailed deer on aspects of biological diversity. These inquiry-based laboratory exercises generated scientifically relevant data and gave students a chance to experience and participate in ongoing scientific research while demonstrating the utility of computer science in the scientific process.