Quantitative skills (statistics, mathematics, and computing) are essential parts of an academic and professional portfolio across ecology and evolutionary biology (EEB). Quantitative Reasoning is also identified as one of five fundamental competencies students are expected to develop through their FAS programs. In EEB disciplines, the statistical computing language R is one of the most common programming languages and means of conducting quantitative analyses. For this project, we focused on improving the experience of undergraduate students and course instructors by scaffolding R coding and analysis skills throughout the EEB program and developing a program-specific pedagogical online resource. The project aligns with the divisional goals of enhancing academic programming and the student experience by better preparing students to enter an increasingly quantitative and data-focused world and the institutional goal to increase data science literacy.
Outcomes
With the support of LEAF, we:
- supported faculty to revise or create data activities and labs that use R across courses from second to fourth year and for courses large (>1000 students) and small (<15 students);
- created an online R Manual that students begin using in second year and that includes modules to support them through fourth-year courses and into independent research projects; and
- created a series of workshops and supporting open office hours for fourth year independent research project students which allowed students with different skill sets to approach independent research with more confidence and competence.