NEON Data Education Fellows are proponents of using data in the classroom and teaching strong quantitative skills along with ecological concepts. All NEON Data Education Fellows participated in a five month long Faculty Mentoring Network focused on creating or modifying and implementing teaching materials using NEON data with their students. Upon completion of the NEON Data Education FMN, these Fellows published thier Open Educational Resource on QUBESHub or another public resource. All of these resources are freely available for other instructors to modify and implement with their own students.
Madeleine Bonsma-Fisher | Fall 2018
University of Toronto
Madeleine Bonsma-Fisher is a PhD Candidate at the University of Toronto in the Department of Physics. She studies bacteria-virus interactions and the role of the CRISPR adaptive immune system in communities of microorganisms. She is passionate about sharing programming skills, and is a founding member of UofT Coders, a campus group dedicated to peer-led learning for quantitative science. Her QUBES module is a portion of an undergraduate ecology course in reproducible quantitative methods co-taught with other graduate students from diverse research backgrounds.
Nancy Cowden | Spring 2018
University of Lynchburg
Nancy Cowden is an Associate Professor of Biology and curator of the Ramsey-Freer Herbarium at the University of Lynchburg. Her teaching and research interests focus on plant evolutionary ecology, especially population-level implications of plant-pollinator interactions. This adaptation of a NEON tutorial grew out of her desire to introduce upper-level students to R as a tool for exploring large data sets as a way to develop research questions that could be further examined on a local scale.
Chris Gough | Spring 2018
Virginia Commonwealth University
Chris Gough is Assistant Professor of Biology at Virginia Commonwealth University in Richmond, Virginia. His primary areas of research and instructional expertise are in terrestrial carbon cycling and forest ecology. The motivation behind his QUBES project module is a career-long reliance on open data from science networks, and recognition that ecology students have an unprecedented, but sometimes daunting, opportunity to apply this relatively new source of data to novel ecological questions. His module endeavors to inspire students to consider the opportunities and challenges afforded by these emergent open datasets.
Teaching Materials: Environmental Drivers of Ecosystem Carbon Fluxes from Minutes to Years
Jackie Hatala Matthes | Spring 2018
Jackie Hatala Matthes is an Assistant Professor of Biological Sciences and Advisory Faculty in Environmental Studies at Wellesley College. Her research focuses on feedbacks between ecosystem processes, climate change, and introduced insects and pathogens. She incorporates data and models into her courses at Wellesley to foster data literacy and computational skills. For the NEON FMN, she developed an app hosted on QUBES that visualizes phenology data from three NEON oak sites and an in-class exercise that uses this app.
Teaching Materials: Outstanding Oaks: Quercus Phenology at NEON Sites
Ahmed Hasan | Fall 2018
University of Toronto
Ahmed Hasan is a PhD candidate in the Department of Cell and Systems Biology at the University of Toronto. His work focuses on understanding how meiotic recombination interacts with drift and selection to shape genome evolution. His QUBES module is part of a graduate student-led course aimed at teaching reproducible methods in R at the undergraduate level.
Raisa Hernández Pacheco | Spring 2018
University of Richmond
Raisa Hernández Pacheco is a postdoctoral fellow in the department of Biology at the University of Richmond, Virginia where she teaches introductory biology and mentors research students. Her primary area of research are in animal population ecology. Her motivation to work on NEON data through QUBES relied on her interest in helping developing data skills among her students. Her module adaptation introduces students to useful data management exercises for a good large dataset icebreaker.
Tyson Lee Swetnam | Spring 2018
University of Arizona
Tyson Swetnam is a data scientist with CyVerse, located at the University of Arizona. His research career started as a fire management specialist for the USDA Forest Service and Rocky Mountain Tree Ring Research. He has a background in ecology, natural resource management, and dendrochronology with a strong emphasis on GIS and remote sensing. His FMN project involved creating tutorials for CyVerse cyberinfrastructure as a data science workbench for NEON AOP data.
Teaching Materials: CyVerse Tutorials for NEON Data Science Institute 2018