Integrate Ocean Observing Initiative (OOI) Data into Research and Teaching: Results from Workshops for Early Career Scientists
Poster Session Part of
Wednesday
Authors
Janice McDonnell, Rutgers University-New Brunswick
Ellen Altermatt, Carleton College
Sage Lichtenwalner, Rutgers University-New Brunswick
Scott Glenn, Rutgers University-New Brunswick
Michael Crowley, Rutgers University-New Brunswick
Lianna Vaccari, Consortium for Ocean Leadership
Funded by the National Science Foundation (NSF), the Ocean Observatories Initiative (OOI) has constructed the observational and computational infrastructure needed to provide sustained measurements of complex oceanographic properties and processes. In 2018, the OOI hosted four workshops for early-career scientists. The workshops were discipline-specific (physics, biology, geology, and chemistry) and were designed to support these scientists in using OOI data in their work through the development of programming, data analysis, and evaluation skills. As part of the workshop, each participant created a Data Validation Report to analyze the quality of one or more OOI instruments.
End-of-workshop surveys were used to provide a summative evaluation of the 2018 workshops. A total of 44 early career scientists participated in the four workshops. Participants in all four workshops reported substantial gains, from before the workshop to after the workshop, in their understanding of and ability to access OOI data, in their ability to process and visualize data in Python, in their ability to evaluate the quality of OOI datasets, in the likelihood that they would use OOI data in their research, and in the relationships they formed with other early career scientists. Based on these outcomes, a new set of workshops was developed for 2019, including four week-long workshops and three mini workshops. Early indicators are that the 2019 workshops are yielding similarly positive outcomes as participants work to learn about OOI's collection of 30 classroom-ready data labs, to develop new applications of OOI data, and to more fully adopt the types of active, reflective, data-intensive teaching strategies that promote student interest in and motivation for scientific inquiry (National Research Council, 2012).
End-of-workshop surveys were used to provide a summative evaluation of the 2018 workshops. A total of 44 early career scientists participated in the four workshops. Participants in all four workshops reported substantial gains, from before the workshop to after the workshop, in their understanding of and ability to access OOI data, in their ability to process and visualize data in Python, in their ability to evaluate the quality of OOI datasets, in the likelihood that they would use OOI data in their research, and in the relationships they formed with other early career scientists. Based on these outcomes, a new set of workshops was developed for 2019, including four week-long workshops and three mini workshops. Early indicators are that the 2019 workshops are yielding similarly positive outcomes as participants work to learn about OOI's collection of 30 classroom-ready data labs, to develop new applications of OOI data, and to more fully adopt the types of active, reflective, data-intensive teaching strategies that promote student interest in and motivation for scientific inquiry (National Research Council, 2012).