Our objective is to develop stand-alone, modular classroom activities for undergraduate students that use publicly-available, long-term, and high-frequency datasets to explore the core concepts of macrosystems ecology while developing quantitative literacy.
The Macrosystems EDDIE modules are specifically designed to help students achieve the following pedagogical goals:
- Improve students' ability to understand and predict how local, regional, and continental processes interact to mediate responses to human activities
- Gain computational skills through engagement in simulation modeling, computer programming, distributed computing, and the analysis of large datasets
- Develop hypotheses, conduct inquiry-based studies to test them, and evaluate if their hypotheses are supported or rejected by data
During 2017-2022, we will be using pre- and post-module student questionnaires and soliciting instructor feedback to assess whether our Macrosystems EDDIE modules are achieving their pedagogical goals. These assessments will allow us to determine whether the modules are helping increase students' understanding of macrosystems ecology and ecological forecasting and will allow us to revise modules as needed to maximize their utility to instructors and students. Previous assessments of modules through Project EDDIE found that students who completed EDDIE modules had significantly improved data manipulation skills, an increased understanding of how to use large datasets, and a greater appreciation for the value of high-resolution and long-term data. Thus, in addition to developing critical quantitative and modeling skills, working with high-frequency sensor datasets cements the real-world application of basic ecological concepts.