Harnessing open science practices to teach ecology and evolutionary biology using interactive tutorials

Abstract

Open science skills are increasingly important for a career in ecology and evolutionary biology (EEB) as efforts to make data and analyses publicly available continue to become more commonplace. While learning core concepts in EEB, students are also expected to gain skills in conducting open science to prepare for future careers. Core open science skills like programming, data sharing, and practices that promote reproducibility can be taught to undergraduate students alongside core concepts in EEB. Yet, these skills are not always taught in biology undergraduate programs, and a major challenge in developing open science skills and learning EEB concepts simultaneously is the high cognitive load associated with learning multiple disparate concepts at the same time. One solution is to provide students with easily digestible, scaffolded, pre-formatted code in the form of vignettes and interactive tutorials. Here, we present six open source teaching tutorials for undergraduate students in EEB. These tutorials teach fundamental ecological concepts, data literacy, programming (using R software), and analysis skills using publicly available datasets while introducing students to open science concepts and tools. Spanning a variety of EEB topics and skill levels, these tutorials serve as examples and resources for educators to integrate open science tools, programming, and data literacy into teaching EEB at the undergraduate level.

Keywords: R programming; cognitive load theory; educational resources; online tutorials; open science; student‐centered learning; teaching; undergraduate education.

FIGURE 1

Schematic of the goals, processes, and summary of the teaching tutorials created as part of the Living Data Tutorials. The upper panel shows the overarching goal to link open science in research and open science in teaching, the middle panel shows the process of tutorial development (data exploration, conceptual exploration, tutorial objectives, and tutorial format), and the lower panel shows the six undergraduate teaching tutorials.

FIGURE 2

Summary of content, examples, and knowledge testing questions covered in the tutorial, “Community Ecology: Hemlock Looper Outbreak on Anticosti Island”. (a) Students interpret community ecology plots by describing tree communities using box plots of species' abundances and using bar graphs to estimate the proportion of each tree species that was damaged by the hemlock looper (Objective 1). (b) Students evaluate the hemlock looper's tree species preferences by plotting tree species' mortality against tree species' abundance (Objective 2). (c) Students make management recommendations in other geographical regions based on information covered throughout the tutorial and suggested videos provided in this section (Objective 3).

FIGURE 3

“Understanding Biodiversity with Metrics & Rank Abundance Curves” tutorial content and examples of the material and exercises. Students are taught to (a) identify, calculate, and implement commonly used metrics (richness, Shannon and Simpson diversity, and evenness) to quantify biodiversity (Objective 1), (b) understand and create rank abundance curves to visualize biodiversity (Objective 2), and (c) use the R package “codyn” to calculate diversity metrics and plot over time to visualize biodiversity change following disturbance (Objective 3).