UNIVERSITY PARK, Pa. — All of the data produced or used in 2020 was estimated to be about 59 zettabytes, each of which equals a billion terabytes. If each terabyte represents a mile, 59 zettabytes would allow for almost 10 full round trips from Earth to Pluto.
Understanding and managing data requires strong critical thinking and problem-solving skills, skills that are essential for engineering students, according to Rebecca Napolitano, assistant professor of architectural engineering at Penn State. However, contextualized data science courses that teach students to apply such skills to their fields — including the importance of data management for other sectors — are not typically a requirement for students in engineering and other disciplines.
Napolitano leads national multidisciplinary research teams developing curricular framework for data science and workforce development that will be transferrable across engineering disciplines and institutes. The teams recently received two grants totaling $2.25 million: a $1.5 million grant from the National Science Foundation through the Harnessing the Data Revolution solicitation program and a $750,000 grant from the U.S. Department of Energy.
“We don’t have to keep reinventing the wheel,” Napolitano said. “We want to lower the barrier of entry for faculty who want to bring data science into their curriculum. We want it to be easy for professors who don’t have a background in data science to use our framework and just run with it to help their students succeed.”
NSF funding: Impacting students and the community
With the funding from the NSF, Napolitano is collaborating with numerous professors across Penn State and other institutions across the country to build data science curricular framework that will help students make the connection between data science and the impact it has on the engineering industry and their communities — something they are not taught in required engineering courses.
Penn State faculty members Nathan Brown, assistant professor of architectural engineering; Yuqing Hu, assistant professor of architectural engineering; Greg Pavlak, assistant professor of architectural engineering; Ryan Solnosky, associate teaching professor of architectural engineering; Houtan Jebelli, assistant professor of architectural engineering; Robert Kimel, associate teaching professor of materials science and engineering; and Wesley Reinhart, assistant professor of materials science and engineering, are co-principal investigators on the project. The collaborating institutions include Texas A&M, George Mason University, University of New Mexico and Tennessee State University.
Napolitano will lead the team to create course modules that focus on thinking in terms of data science, ethical problem solving and community awareness. She said the course module content will help students understand how data science relates to their specific engineering field and how data science skills can help them make an impact in their communities.
To support the latter goal, the team plans to collaborate with local communities, as well as industry, to help align their curriculum with expectations in the workforce and provide students with the resources for data analysis-focused projects. For example, through an existing connection with the Nittany AI Alliance, students will have the opportunity to examine spatial data from Centre County related to the age of county infrastructure, commercial and residential, and household income per borough. Students will report their findings and what methods they use to examine the data.
“This NSF call for proposals was really focused on this idea of community inclusion and where the data sets are coming from,” Napolitano said. “I hadn’t thought about that before, but when I read through the call, I realized how much more impactful this project would be if we were getting data sets from local community partners.”
Napolitano said the students will be able to see how local businesses and organizations are using the data sets and better understand how to analyze that data.
“The local community is very excited to collaborate with us, and the students are excited to be working with real-life data and not just numbers that I make up,” Napolitano said.
The team will also engage with two K-12 schools that are interested in implementing extracurricular programming and data science experiences for their students. The team plans to provide the resources to more K-12 students in the future.
DOE funding: Impacting students and the environment
With the funding from the DOE, Napolitano and her team — which includes Brown, Hu, Greg Pavlak and Solnosky — will focus specifically on how to frame computational concepts within the context of energy for buildings and how it impacts national laboratories across the country and the energy-related workforce.
The grant program awarded funding to 44 projects, all focused on lowering Americans’ energy bills and helping meet President Joe Biden’s goal of net-zero carbon emissions by 2050 by investing in new energy efficient building technologies, construction practices and the U.S. buildings-sector workforce.
Napolitano’s team will collaborate with the National Renewable Energy Laboratory and existing building engineering-focused programs across numerous institutes — including Penn State, Missouri University of Science and Technology, Illinois Institute of Technology, George Mason University, Oklahoma State University, University of New Mexico, University of Texas at Austin, University of Miami and Tennessee State University — to create a multi-institution consortium for curriculum development, dataset curation and resource sharing that incorporates energy-facing computation and data science into building engineering curricula.
Napolitano’s team will frame the computational course materials around building energy comprehension and how it impacts the energy-related workforce, analyzing the students’ computational comprehension and their understanding of the work that happens at national labs.
Napolitano plans to make the curriculum for both projects web-based, so it can be easily disseminated and eventually made available to anyone wanting to integrate the concepts into their courses. According to Napolitano, the “plug-and-play” format of the curriculum will provide valuable resources for professors and teachers who are not formally trained in data science and computation.
It takes a village
Napolitano said the collaborative nature of Penn State made it easy for her and the team to include so many groups in this project and cover a broad range of topics within data science education.
“One of the reasons I came to Penn State was because everyone is so collaborative,” Napolitano said. “Penn State’s community feel and its ‘it takes a village’ mentality were the reasons these grant proposals were successful, the reason why I absolutely love it here and the reason why these projects will be so impactful.”