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Title: Macrosystems EDDIE Teaching Modules Increase Students’ Ability to Define, Interpret, and Apply Concepts in Macrosystems Ecology
Ecologists are increasingly using macrosystems approaches to understand population, community, and ecosystem dynamics across interconnected spatial and temporal scales. Consequently, integrating macrosystems skills, including simulation modeling and sensor data analysis, into undergraduate and graduate curricula is needed to train future environmental biologists. Through the Macrosystems EDDIE (Environmental Data-Driven Inquiry and Exploration) program, we developed four teaching modules to introduce macrosystems ecology to ecology and biology students. Modules combine high-frequency sensor data from GLEON (Global Lake Ecological Observatory Network) and NEON (National Ecological Observatory Network) sites with ecosystem simulation models. Pre- and post-module assessments of 319 students across 24 classrooms indicate that hands-on, inquiry-based modules increase students’ understanding of macrosystems ecology, including complex processes that occur across multiple spatial and temporal scales. Following module use, students were more likely to correctly define macrosystems concepts, interpret complex data visualizations and apply macrosystems approaches in new contexts. In addition, there was an increase in student’s self-perceived proficiency and confidence using both long-term and high-frequency data; key macrosystems ecology techniques. Our results suggest that integrating short (1–3 h) macrosystems activities into ecology courses can improve students’ ability to interpret complex and non-linear ecological processes. In addition, our study serves as one of the first more » documented instances for directly incorporating concepts in macrosystems ecology into undergraduate and graduate ecology and biology curricula. « less
Authors:
; ;
Award ID(s):
1926050 1737424 1753639 1933016 1702506 1933102
Publication Date:
NSF-PAR ID:
10304367
Journal Name:
Education Sciences
Volume:
11
Issue:
8
ISSN:
2227-7102
Sponsoring Org:
National Science Foundation
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