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Before taking Assistant Professor of Biology Bárbara Bitarello's class "Biostatistics with R" in Fall 2023, Nicole Cavalieri '26 did not think of herself as a programmer. Having mainly taken English classes for her major, she did not consider herself someone interested in computing. “I didn’t think of myself as someone who could do coding—I was pretty intimidated by it.” she recalled. Nevertheless, she had added a Data Sciences minor onto her plan of study, which led to Bitarello's class.

As the class progressed, Bitarello saw a talent within Cavalieri for learning new coding concepts and explaining them to others, "Nicole was extremely dedicated to learning the skills and, at the first opportunity of teaching others, I could tell she had a talent and a joy in doing so. Moreover, during office hours, which she attended often, we had candid conversations about the lessons and the course in general,” Bitarello said. “All of this made me think of Nicole as someone who could work with me in developing these materials and, more broadly, as someone who might thrive in working on pedagogical projects." 

For a course assignment, Cavalieri was tasked with making a tutorial that would teach students how to use R, a programming language useful for storing, transforming, and displaying scientific data. Bitarello was so impressed by Cavalieri’s work that she made an offer: would Cavalieri use her skills on a Digital ����������� (DBM) grant project? During the Summer and Fall 2023, Bitarello had been using her grant from the DBM program—which is designed to increase faculty and students’ knowledge of educational technologies— to work with students part-time on developing teaching resources for the “Biostatistics with R” course. However, she wanted someone to work on it full time this past summer. Would Cavalieri be interested? "It felt really nice that she recognized a skill I had.” Cavalieri recalled. She said yes, and subsequently spent the summer updating and expanding the project. 

The modules Cavalieri made are designed to teach learners new to R how to use it for biological analysis. For them, she developed a series of realistic data problems that participants would have to solve. These included situations where code would break. “(R) is not something you can just memorize or study, you've got to practice," Cavalieri said. "But there are so many things R can do.” While she found public resources to refer to, she also found Bitarello invaluable. “She was very available for advice but trusted us to make our own decisions.” Ultimately, the process helped her to appreciate the issues involved in teaching. “I only knew what it was like to be a student, but now I know what it’s like to be a professor.”  

Going forward, Cavalieri hopes to continue honing her teaching and coding skills. In line with �����������'s Digital Competencies, she wants to make the project, when finished, publicly available. She also is serving as student partner in the and hopes to serve as a TA for ����������� courses. “My work over the summer did inspire me to stay in academia. I did not realize how much I would like to be a teacher," she said, "I definitely want to keep cultivating these data skills.”