Incorporating ESA 4DEE in the development of EREN flexible learning projects using NEON databases
Wednesday, August 4, 2021
ON DEMAND
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Mary Beth Kolozsvary, Environmental Studies and Sciences, Siena College, Loudonville, NY, Laurel J. Anderson, Department of Botany and Microbiology, Ohio Wesleyan University, Delaware, OH, Sandra Cooke, Natural Sciences, Greensboro College, Greensboro, NC, Alycia Crall, NEON Project, Battelle, Boulder, CO, Danielle E. Garneau, Center for Earth and Environmental Science, SUNY Plattsburgh, Plattsburgh, NY, Matthew J. Heard, Biology, Belmont University, Nashville, TN, Alisa A. Hove, Biology, Warren Wilson College, Asheville, NC, Jason Kilgore, Biology Department, Washington & Jefferson College, Washington, PA, Karen Kuers, Sewanee: The University of the South, Timothy S. McCay, Biology and Environmental Studies, Colgate University, Hamilton, NY, Allison Parker, Biological Sciences, Northern Kentucky University, Highland Heights, KY, Jennifer Rhode Ward, University of North Carolina at Asheville and Kaitlin Stack Whitney, Science, Technology, and Society, Rochester Institute of Technology, Rochester, NY
Presenting Author(s)
Mary Beth Kolozsvary
Environmental Studies and Sciences, Siena College Loudonville, NY
Background/Question/Methods The Ecological Research as Education Network (EREN) promotes collaborative ecological research that generates high-quality, publishable data involving faculty and students at primarily undergraduate institutions (PUIs). EREN projects investigate ecological questions using standardized protocols that allow undergraduate students to collect and compare data across multiple sites over broad geographic areas and environmental settings. EREN has a record of supporting highly productive collaborative research projects that fit within the constraints of scientists with significant teaching responsibilities. EREN projects have produced several peer-reviewed publications that approach scientific inquiry through differing vantage points, from focusing on ecological questions to pedagogical elements (e.g., development of instructional materials, assessment). Over the years, EREN has expanded and strengthened in depth and breadth by pursuing partnerships and collaborations with other organizations and networks. For example, EREN is collaborating with the National Ecological Observatory Network (NEON) and Environmental Data-Driven Inquiry & Exploration (Project EDDIE) to support a series of workshops designed to focus on integrating networked large datasets into undergraduate teaching and research. In 2020, the COVID-19 crisis created an urgent need for online educational experiences that teach field ecology concepts to undergraduates in a flexible, socially-distanced context. In response to this pressing need, EREN scientists quickly assembled to develop a proposal for National Science Foundation (NSF) funding to adapt ongoing and new EREN projects into online learning modules to allow data collection in backyards, campuses, and urban areas by students learning remotely. These flexible modules were designed to embed rich learning experiences within authentic ecological research during these disruptive times. Results/Conclusions EREN successfully promoted the availability of these newly-developed instructional materials through webinars, list-serves, and Quantitative Undergraduate Biology Education and Synthesis (QUBES)-supported Faculty Mentoring Networks (Fall 2020, Spring 2021). The flexible projects involve students in collecting data, working with both student-collected and NEON data, and are designed so that students can address a variety of hypotheses at multiple scales of inquiry. EREN scientists recognize and appreciate the importance of the Four-Dimensional Ecology Education (4DEE) framework, and the flexible learning projects were designed to align with those guidelines. The flexible projects were used widely and received positive feedback from instructors who implemented them. The EREN-NEON collaboration, which ties NEON data (collected at the macroscale) with comparable local data in varied settings, is well positioned to explore innovative ways to move the 4DEE framework forward.