Harnessing the power of open-source software for research-integrated learning and assessment

Abstract

Authentic tasks in undergraduate subjects, such as field data collection and analysis, allow students to explore key concepts in the context of real-world problems. In a third-year environmental sciences subject, students learn to interpret highly dynamic systems that underpin ecosystem and food security in our rapidly changing world. Students conduct a survey of pollination networks, analyse and interpret their data as an ecologist would. A challenge to implementing this task was access to specialist software to create the data visualisations (bipartite graphs) for the network analyses. Typically, scientists use R software; however, limited class time means we cannot teach students the programming language required. Third party graphing software is available but requires yearly setup and costs, which are unsustainable as student numbers grow. Our solution was to harness the power of open-source software and develop the Bipartite Network Analysis app using Shiny and Bipartite package for R (DOI: 10.5281/zenodo.1219306). This web-based app removes the barrier of the need for coding experience while introducing students to industry-standard software. Students create journal-quality bipartite graphs using their own data and complete in-depth investigations of plant-animal network properties. Our authentic task and app facilitate students’ learning of the disciplinary skills required by environmental scientists.