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An Assessment of Simulation-Based Learning Modules in an Undergraduate Engineering Economy Course

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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

17

DOI

10.18260/1-2--41913

Permanent URL

https://peer.asee.org/41913

Download Count

493

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Paper Authors

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Ashkan Negahban Pennsylvania State University, Great Valley

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ASHKAN NEGAHBAN, Ph.D., is an Assistant Professor of Engineering Management at the School of Graduate Professional Studies at The Pennsylvania State University (USA). He received his Ph.D. and master’s degrees from Auburn University (USA) and his BS from University of Tehran (all in Industrial and Systems Engineering). His research involves stochastic simulation methods, primarily agent-based and discrete-event simulation. He also conducts research related to novel simulation-based learning environments in STEM education. His email and web addresses are anegahban@psu.edu and https://ashkannegahban.com.

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Omar Ashour Pennsylvania State University, Behrend College Orcid 16x16 orcid.org/0000-0003-3775-6445

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Dr. Omar Ashour is an Associate Professor of Industrial Engineering at Pennsylvania State University, The Behrend College. Dr. Ashour received a B.S. degree in Industrial Engineering/Manufacturing Engineering and an M.S. degree in Industrial Engineering from Jordan University of Science and Technology (JUST) in 2005 and 2007, respectively. He received his M.Eng. degree in Industrial Engineering/Human Factors and Ergonomics and a Ph.D. degree in Industrial Engineering and Operations Research from The Pennsylvania State University (PSU) in 2010 and 2012, respectively. Dr. Ashour was the inaugural recipient of William and Wendy Korb Early Career Professorship in Industrial Engineering in 2016. Dr. Ashour’s research areas include data-driven decision-making, modeling and simulation, data analytics, immersive technologies, and process improvement. He contributed to research directed to improve design and engineering education. Dr. Ashour currently serves as a Technical Vice President (TVP) on the Technical Operations Board (TOB) of the Institute of Industrial and Systems Engineers (IISE).

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Mahgol Nowparvar Pennsylvania State University, Great Valley

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Mahgol Nowparvar graduated with M.S in Data analytics from Penn State Great Valley. Her research interests are in immersive technologies, virtual reality, augmented reality, and artificial intelligence.

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Daniel Knight University of Colorado Boulder

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Dr. Sabahattin Gokhan Ozden is an Assistant Professor of Information Sciences and Technology at Penn State Abington. He holds a Ph.D. in Industrial and Systems Engineering from Auburn University. He graduated from MISE program in Auburn University Industrial and Systems Engineering Department in 2012. He has a Bachelor of Science in Software Engineering and a Double Major in Industrial Systems Engineering from Izmir University of Economics. He is a two times recipient of the Material Handling Education Foundation, Inc. Scholarship. His research has been awarded by National Science Foundation, Penn State Strategic Initiative Seed Grant, Penn State Social Science Research Institute, Penn State Justice Center for Research, and Penn State Abington Chancellor’s grant.

His research interests include facility logistics, heuristic optimization, sequencing and scheduling, simulation, model driven engineering, and engineering education.

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Parhum Delgoshaei Pennsylvania State University

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Abstract

We propose and assess the effectiveness of novel immersive simulation-based learning (ISBL) modules for teaching and learning engineering economy concepts. The proposed intervention involves technology-enhanced problem-based learning where the problem context is represented via a three-dimensional (3D), animated discrete-event simulation model that resembles a real-world system or situation that students may encounter in future professional settings. Students can navigate the simulated environment in both low- and high-immersion modes (i.e., on a typical personal computer or via a virtual reality headset). The simulation helps contextualize and visualize the problem setting, allowing students to observe and understand the underlying dynamics, collect relevant data/information, evaluate the effect of changes on the system, and learn by doing. The proposed ISBL approach is supported by multiple pedagogical and psychological theories, namely the information processing approach to learning theory, constructivism theory, self-determination theory, and adult learning theory. We design and implement a set of ISBL modules in an introductory undergraduate engineering economy class. The research experiments involve two groups of students: a control group and an intervention group. Students in the control group complete a set of traditional assignments, while the intervention group uses ISBL modules. We use well-established survey instruments to collect data on demographics, prior preparation, motivation, experiential learning, engineering identity, and self-assessment of learning objectives based on Bloom’s taxonomy. Statistical analysis of the results suggests that ISBL enhances certain dimensions related to motivation and experiential learning, namely relevance, confidence, and utility. We also provide a qualitative assessment of the proposed intervention based on detailed, one-on-one user testing and evaluation interviews.

Negahban, A., & Ashour, O., & Nowparvar, M., & Knight, D., & Ozden, S., & Delgoshaei, P. (2022, August), An Assessment of Simulation-Based Learning Modules in an Undergraduate Engineering Economy Course Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41913

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