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Cloud technologies for scalable engagement and learning in flipped classrooms

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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

Civil Engineering Division - The New Normal: Enduring Technology Improvements in the Classroom

Page Count

8

DOI

10.18260/1-2--40811

Permanent URL

https://peer.asee.org/40811

Download Count

344

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Paper Authors

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Sotiria Koloutsou-Vakakis University of Illinois at Urbana - Champaign

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Sotiria Koloutsou-Vakakis (Ph.D.) is a Senior Lecturer and Research Scientist in Civil and Environmental Engineering, at the University of Illinois at Urbana-Champaign. She holds degrees in Civil-Surveying Engineering, Geography and Environmental Engineering. Her most recent research is about gaseous emissions of reactive nitrogen from fertilized fields into the atmosphere and impacts on air quality and climate change. She teaches undergraduate and graduate courses on Air Quality, Science and Environmental Policy, and Engineering Risk and Uncertainty and is active with K-12 outreach. She has strong interest in engineering education. She develops materials and researches best practical classroom approaches for integrating computation and computational thinking in introductory CEE courses; and for promoting teamwork, communication and problem-solving in context, throughout the CEE curriculum.

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Christopher Tessum

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Eleftheria Kontou

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Hadi Meidani

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Hadi Meidani is an Associate Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. He obtained his Ph.D. in Civil Engineering and his M.S. in Electrical Engineering from the University of Southern California (USC) in 2012 and also a M.S. in Structural Engineering from USC. After his Ph.D. he was a postdoctoral research associate in the Department of Aerospace and Mechanical Engineering at USC in (2012-2013) and in the Scientific Computing and Imaging Institute at the University of Utah (2013-2014). He is the recipient of the NSF CAREER Award to study fast computational models for energy-transportation systems. His research interests are uncertainty quantification, scientific machine learning, computational modeling of civil infrastructure systems, and resilient infrastructures.

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Lei Zhao

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Dr. Lei Zhao is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research concerns the physical and engineering processes in the Atmospheric Boundary Layer where most human activities and environmental systems are concentrated, with a particular focus on built surfaces and urban environments. He combines theory, numerical modeling, remote sensing and in situ observations, and cutting-edge machine learning methods to study environmental fluid mechanics and land-atmosphere dynamics that relate to urban environments, climatology and hydrology, climate change, climate impacts and adaptation. He received his Ph.D. (2015) in Atmospheric and Environmental Science from School of the Environment at Yale University. Before joining at UIUC, Dr. Zhao was a postdoctoral research fellow in the Program in Science, Technology and Environmental Policy (STEP) at Princeton University. Dr. Zhao obtained his B.S. degree (2009) in Physics and Atmospheric Physics from Nanjing University in China.

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Abstract

Recent innovative updates of two required second year civil and environmental engineering courses focus on integration of computational thinking and student engagement, within a student-centered learning classroom environment. As part of the effort, we adopted use of an online open source problem solving platform that emphasizes mastery. This environment has enabled us to develop approaches and materials that work well for remote as well as in person teaching.

In this paper, we demonstrate materials and approach for increasing in-class student engagement and teamwork. Emphasis is on decreasing cognitive load during class time. In the past, students used Python or R to solve problems and submit their answers for auto-grading in the online platform. To complete an activity, students needed to switch among at least three windows on their laptops for the online environment, the software and the worksheet. In addition, often there were issues specific to student laptop causing distraction away from a given class activity.

Recent contributions to the open-source online platform enabled use of Jupyter workspaces. Use of the workspaces helps reducing cognitive overload by reducing window and context switching; it is operating system and hardware neutral; students can understand the theory through simulation and visualization with code they complete; teamwork is supported regardless of student location; and it works well in small or big classes. A demonstration class space is available to interested audience who wish to gain the online experience with an example activity.

Koloutsou-Vakakis, S., & Tessum, C., & Kontou, E., & Meidani, H., & Zhao, L. (2022, August), Cloud technologies for scalable engagement and learning in flipped classrooms Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40811

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