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A modular approach for integrating data science concepts into multiple undergraduate STEM+C courses

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Conference

2022 ASEE Annual Conference & Exposition

Location

Minneapolis, MN

Publication Date

August 23, 2022

Start Date

June 26, 2022

End Date

June 29, 2022

Conference Session

NSF Grantees Poster Session

Page Count

20

DOI

10.18260/1-2--42010

Permanent URL

https://peer.asee.org/42010

Download Count

407

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Paper Authors

biography

Kang Xia

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Kang Xia received her Ph.D. from the University of Wisconsin-Madison (1997), M.S. from Louisiana State University (1993), and B.S. from Beijing Agricultural University (1989). She was a Postdoctoral Researcher at the University of Wisconsin-Madison (1997-1998), an Assistant Professor at Kansas State
University (1998-2001), University of Georgia (2002-2005), and Assistant Professor, Dept. of Chemistry, Mississippi State University (2006-2010), an Associate Professor at Mississippi State University (2010-2011) and at Virginia Tech (2011-2016). She also served as Director for Re-search Division and
Industrial and Agricultural Services Division, Mississippi State Chemical Laboratory (2006-2011). She is currently a Professor at Virginia Tech (2016-present). She has served as adhoc reviewer for a number of scientific
journals and funding agencies. She served as associate editor for the Journal of Environmental Quality and the Soil Science Society of America Journal. She is an expert on method development for analysis of
organic chemicals in environmental matrixes and environmental occurrence, fate, and impact of organic chemicals. She has successfully managed and accomplished close to $11 million federal and state funded
interdisciplinary environmental projects. She has published 73 peer-reviewed papers, 6 book chapters, and given 126 professional presentations. She holds membership of the American Chemical Society , the Soil Science Society of America, and SigmaXi.

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Mohammad Yunus Naseri Virginia Polytechnic Institute and State University

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Yunus Naseri is a Ph.D. student in the Department of Civil and Environmental Engineering at Virginia Tech. He received his BEng in civil engineering from Herat University, Herat, Afghanistan in 2015. Through a Fulbright Foreign Student Program scholarship, he completed his MS in civil engineering from Virginia Tech between the years 2018 - 2020. He has more than three years of productive experience in teaching at different academic levels and subjects. His doctoral research focuses on data science literacy for undergraduates and applications of data-driven methods in solving complex civil engineering challenges.

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Gautam Biswas Vanderbilt University

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Gautam Biswas conducts research in Intelligent Systems with primary interests in monitoring, control, and fault adaptivity of complex cyber-physical systems. In particular, his research focuses on Deep Reinforcement Learning, Unsupervised and Semi-supervised Anomaly Detection methods, and Online Risk and Safety analysis applied to Air and Marine vehicles as well as Smart Buildings. His work, in conjunction with Honeywell Technical Center and NASA Ames, led to the NASA 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning System and Data Mining methods to improve aircraft diagnostic and prognostic systems.

Prof. Biswas is also involved in developing intelligent open-ended learning environments focused on learning and instruction in STEM domains that adapt to students’ learning performance and behaviors. He has also developed innovative learning analytics and data mining techniques for studying students’ learning behaviors and linking them to their metacognitive and self-regulated learning strategies. His research is supported by funding from the Army, NASA, and NSF. He has published extensively and currently has over 600 refereed publications. He is a Fellow of the IEEE Computer Society, Asia Pacific Society for Computers in Education, and the Prognostics and Health Management society.

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Manoj Jha North Carolina Agricultural and Technical State University (CoE)

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Dr. Manoj K Jha is a professor in the Civil, Architectural, and Environmental Engineering department at the North Carolina A&T State University. His research interests include hydrology and water quality studies for water resources management under land use change and climate change. His educational research interests include critical thinking and active learning.

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Erin Henrick Vanderbilt University

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Erin Henrick is a lecturer in the Department of Leadership, Policy, and Organization at Peabody College of Vanderbilt University. Dr. Henrick is also president of Partner to Improve, an education research and consulting group supporting improvement and systemic change in education through powerful partnerships. Dr. Henrick is an Research Practice Partnerships (RPPs) researcher, evaluator, and professional development provider. Prior to evaluating RPPs, Dr. Henrick was a researcher on a 10 year NSF funded RPP (known as MIST) focused on improving math instruction across large urban districts. She co-authored the book Systems for Instructional Improvement-Creating Coherence from the Classroom to the District Office. Dr. Henrick received her Ed.D. in Leadership, Policy, and Organization from Vanderbilt University.

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Emily Kern

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Caitlin Snyder

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Caitlin Snyder is a PhD student in the department of Computer Science at Vanderbilt University. Her research focuses on understanding and supporting students' collaborative knowledge co-construction during computational modeling.

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Landon Marston Virginia Polytechnic Institute and State University

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Dr. Landon Marston is an assistant professor in Civil and Environmental Engineering at Virginia Tech.

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Abhishek Dubey

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Bio: Dr. Abhishek Dubey is an Assistant Professor of Electrical Engineering and Computer Science at Vanderbilt University, Senior Research Scientist at the Institute for Software-Integrated Systems. Abhishek directs the SCOPElab (https://scopelab.org/) at the Institute for Software Integrated Systems and is the co-lead of the Vanderbilt Initiative for Smart Cities Operation and Research (VISOR). His broad research interest is in the design and operation of decision procedures for smart and connected communities with a focus on transportation and energy networks. In particular, he focuses on the design and operation of Cyber-physical Systems (CPS) with Artificial Intelligence (AI) based components (AI-CPS) with a focus on public transit systems, emergency response systems, and power grids. For these systems, his lab investigates the principled design, operation, and optimization methods that not only consider the system operations but also consider resilience, performance, and assurance. Some of his key research results include the design of hierarchical decision procedures for responding to motor vehicle crashes, the design of energy-efficient transit operation procedures, and the design of transactive energy systems. His recent publications can be obtained from his lab’s publication page. His work has been funded by NSF, NASA, DOE, and ARPA-E. AFRL, DARPA, Siemens, Cisco, and IBM. Abhishek completed his Ph.D. in Electrical Engineering from Vanderbilt University in 2009. He received his M.S. in Electrical Engineering from Vanderbilt University in August 2005 and completed his undergraduate studies in Electrical Engineering from the Indian Institute of Technology, Banaras Hindu University, India, in May 2001.

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Christopher Vanags

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Chris Vanags is the Director of the Peabody Research Office in Vanderbilt's Peabody College of Education and a Research Assistant Professor in the Department of Earth and Environmental Sciences. He is keenly interested in connecting primary scientific research to novel educational experiences with the goal of increasing the STEM pipeline for students from diverse backgrounds. His primary role in the Dean’s office is to support Peabody research initiatives by creating affinity groups of like-minded faculty from across campus to tackle large-scale problems, building relationships with internal and external organizations and educational institutions, and identifying and creating resources to catalyze and inform research on education and human development.

As the Associate Director of the Center for Science Outreach and one of the founding faculty members of the School for Science and Math at Vanderbilt, he helped to develop and implement STEM enrichment programs which are grounded in the practice of learning through the generation of primary knowledge. With funding from three consecutive NIH Science Education Partnership Awards, this model has been adapted in different ways to serve thousands of middle school and high school students across the district. He drew from this model to form the basis of an international educational reform effort for 173 schools in the Emirate of Abu Dhabi in the United Arab Emirates. This three year project resulted in the creation of two STEM-based model schools, a reformation of all science and mathematics standards and the creation of thirteen high school courses with aim to improve student retention and increase the STEM workforce.

His work is supported by three different NSF awards to improve access to Computer Science for middle and high school students, increase the pipeline of underrepresented minority students into the geosciences, and improve the ways that we use data to inform decision making. He is also supported by an NIH award to translate intellectual and developmental disability research into practice.

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Niroj Aryal

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Dr. Niroj Aryal is an assistant professor of Biological Engineering at the Department of Natural Resources and Environmental Design at the North Carolina A and T State University. His academic background includes a bachelor’s in Agricultural Engineering from Tribhuvan University, a postgraduate diploma in Environmental Education and Sustainable Development from Kathmandu University, a master’s in Biosystems Engineering from Michigan State University and a dual-major doctorate in Biosystems Engineering and Environmental Engineering from Michigan State. Dr. Aryal’s research interests are in water quality, hydrology, phytoremediation, agricultural conservation practices, urban best-management practices (BMPs), and ecological engineering. Pertaining to education, his interests are in innovative instructional techniques to enhance student motivation and learning.

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Steven Jiang North Carolina Agricultural and Technical State University (CoE)

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Dr. Steven Jiang is an Associate Professor in the Department of Industrial and Systems Engineering at North Carolina A&T State University. His research interests include Human Systems Integration, Visual Analytics, and Engineering Education.

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Erin Hotchkiss

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Dr. Erin R. Hotchkiss is an Assistant Professor in the Department of Biological Sciences and a Faculty Affiliate of the Global Change Center at Virginia Tech. She received her Ph.D. in Ecology from the University of Wyoming, a M.Sc. in Zoology and Physiology from the University of Wyoming, and a B.Sc. in Environmental Studies with a minor in Sociology from Emory University. Prior to joining Virginia Tech, she worked as a postdoctoral fellow at Umeå University, Sweden and Université du Québec à Montréal, Canada. Ongoing research in the Hotchkiss Lab (www.hotchkisslab.com) is using environmental sensors, stable isotope tracers, whole-ecosystem experiments, and process-based modeling to explore how environmental change, land-water interactions, and ecosystem processes shape the transport, transformation, and fate of carbon, nutrients, and pollutants in freshwaters.

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Vinod Lohani Virginia Polytechnic Institute and State University

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Dr. Vinod K Lohani is a Professor of Engineering Education at Virginia Tech. He is currently serving as a Program Director at the National Science Foundation and is assigned to NSF Research Traineeship (NRT), Innovations in Graduate Education (IGE), and CAREER programs.

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Brendan McLoughlin Virginia Polytechnic Institute and State University

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Brendan McLoughlin in second-year Master's student in the School of Plant and Environmental Sciences at Virginia Tech. His research focuses on the detection and quantification of drugs of abuse in domestic wastewater, and the fate of those drugs in the environment post-wastewater treatment.

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Sambridhi Bhandari

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Sambridhi Bhandari is a first year master's student pursuing Civil Engineering at North Carolina Agricultural & Technical University. She received her undergraduate degree in Civil Engineering from Uttrakhand Technical University in 2019. Her research interest is in application of machine learning and data science in hydrology, environmental engineering, and improving the education system.

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Abstract

With increasingly technology-driven workplaces and high data volumes, instructors across STEM+C disciplines are integrating more data science topics into their course learning objectives. However, instructors face significant challenges in integrating additional data science concepts into their already full course schedules. Streamlined instructional modules that are integrated with course content, and cover relevant data science topics, such as data collection, uncertainty in data, visualization, and analysis using statistical and machine learning methods can benefit instructors across multiple disciplines. As part of a cross-university research program, we designed a systematic structural approach–based on shared instructional and assessment principles–to construct modules that are tailored to meet the needs of multiple instructional disciplines, academic levels, and pedagogies. Adopting a research-practice partnership approach, we have collectively developed twelve modules working closely with instructors and their teaching assistants for six undergraduate courses.

We identified and coded primary data science concepts in the modules into five common themes: 1) data acquisition, 2) data quality issues, 3) data use and visualization, 4) advanced machine learning techniques, and 5) miscellaneous topics that may be unique to a particular discipline (e.g., how to analyze data streams collected by a special sensor). These themes were further subdivided to make it easier for instructors to contextualize the data science concepts in discipline-specific work. In this paper, we present as a case study the design and analysis of four of the modules, primarily so we can compare and contrast pairs of similar courses that were taught at different levels or at different universities. Preliminary analyses show the wide distribution of data science topics that are common among a number of environmental science and engineering courses. We identified commonalities and differences in the integration of data science instruction (through modules) into these courses. This analysis informs the development of a set of key considerations for integrating data science concepts into a variety of STEM + C courses.

Xia, K., & Naseri, M. Y., & Biswas, G., & Jha, M., & Henrick, E., & Kern, E., & Snyder, C., & Marston, L., & Dubey, A., & Vanags, C., & Aryal, N., & Jiang, S., & Hotchkiss, E., & Lohani, V., & McLoughlin, B., & Bhandari, S. (2022, August), A modular approach for integrating data science concepts into multiple undergraduate STEM+C courses Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--42010

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