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Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.

The COVID‐19 pandemic significantly impacted undergraduate education and fundamentally altered the structure of course delivery in higher education. In field‐based biology and ecology courses, where instructors and students typically work collaboratively and in‐person to collect data, this has been particularly challenging. In this context, faculty from the Ecological Research as Education Network (EREN) collaborated with the National Ecological Observatory Network (NEON) to design five free‐flexible learning projects for use by instructors in varied modalities (e.g., socially distanced in‐person, remote, or HyFlex). The five flexible learning projects incorporated the Ecological Society of America’s 4DEE framework and included field data collection, data analysis components, and an activity that incorporates existing NEON field protocols or datasets. Each project was designed to provide faculty members with a high degree of flexibility so that they could tailor the implementation of the projects to fit course‐specific needs. Collectively, these learning projects were designed to be flexible, inclusive, and facilitate hands‐on research while working in alternative classroom settings.