Using high volumes of data for research and education increases both opportunities and challenges to analyze and synthesize scientific understanding. A growing number of research programs collect high volumes of data, especially oceanography programs where the use of advanced technologies, including cabled systems, autonomous gliders, and sophisticated buoy sensor systems generate huge data sets. For example, the National Science Foundation's Ocean Observatories Initiative (OOI) has constructed observational and computer infrastructure that provides sustained ocean measurements to study climate variability, ocean circulation, ecosystem dynamics, air-sea exchange, seafloor processes, and plate-scale geodynamics for the coming decades. This ocean observing system is already advancing our ability to understand the natural world by accumulating large quantities of data to address questions about complex oceanographic processes. This expanded access to data also provides professors in the geosciences with unprecedented opportunities to engage undergraduate students in data experiences using real-world data sets, models, and simulations of geoscience processes using web-based technologies.
Learning directly from data has been shown to be advantageous as it challenges learners to construct meaning and develop a deeper understanding of a topic or phenomenon, encourages student inquiry, and develops skills with the practices of science. Using real world data has also been shown to help develop interest in, motivation for, and identity with respect to science. Moreover, analyzing data and identifying patterns have become core workforce skills in the workplace and for civic engagement in the 21st century. The OOI offers an opportunity to bring professionally collected, real-time and near-real-time data, images, and video of the Earth's oceans into both formal and informal learning environments. This project builds on prior efforts to create cyberinfrastructure that helps make OOI data available to educators. In order to correctly focus development of educational tools, two front-end evaluation studies on the practices and teaching needs of the oceanographic community were conducted. While 73% of undergraduate professors said they use data in their classroom, only a small subset use real-time data with their students. Most importantly, it was determined that there is a need for further exploration into how to effectively integrate data into teaching and how to create data visualization tools that help undergraduate professors meet the demands of teaching 21st century science skills and practices. In order to meet the challenges posed by teaching with authentic data and to encourage the use of OOI data in undergraduate classrooms, this project will design and implement professional development workshops and a mini grant program to expand the use of OOI data in undergraduate teaching.
This project further develops, scales up, and implements ways to improve undergraduate student engagement in the geosciences through classroom experiences focused on analyzing oceanographic data. The PIs will engage approximately 150 faculty in workshops focused on teaching with OOI data and data visualizations. Faculty from community colleges, Primarily Undergraduate Institutions (PUIs), Minority-Serving Institutions (MSIs), Historically Black Colleges & Universities will be recruited, as well as faculty from research laboratories, larger research universities, and a team of pedagogical experts. The goal of this project is to expand the community of professors effectively utilizing OOI data in their classrooms, eventually creating an OOI focused Community of Practice for teaching with data. The project will support a variety of activities and workshops that will increase the involvement of faculty members from a wide range of institutions in the OOI user community. The faculty will be able to use OOI data products to engage students in oceanography via online data activities and improve the training of undergraduate students in data interpretation and analysis. Data explorations will be developed by collaborating undergraduate professors and made available for all educators to use. The project will assess and evaluate the effectiveness of various methods for introducing data into the classroom and for training faculty members in the new methods.
This project addresses NSF priorities as stated in the NSF Strategic Plan for 2018-2022, "Strategic Objective 2.2 - STEM Workforce: Foster the growth of a more capable and diverse research workforce and advance the scientific and innovation skills of the Nation."
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
