2025 ASEE Annual Conference & Exposition

Work in Progress: A Second Comparative Study of the Impact of Virtual Reality in Aerospace Education

With the increasing accessibility of virtual reality (VR) technology, its potential for enhancing classroom learning has gained attention. While its use in higher education is still in its experimental stage, particularly at the college level, preliminary research suggests that VR can improve student learning outcomes. In aerospace engineering, VR offers unique opportunities for students to interact with complex, large-scale aerospace systems, visualize three-dimensional phenomena, and better comprehend environmental contexts that are otherwise difficult to experience in traditional classroom settings.

This paper presents the design and execution of an experimental course aimed at undergraduate aerospace engineering students to assess the educational impact of VR. Core aerospace engineering concepts are taught through a combination of lectures and lab activities. For each class, a lecture is followed by an activity in VR. In this version of the course, new content and topics are introduced.

To evaluate the effectiveness of VR in the course, a combination of qualitative and quantitative data will be collected. Pre- and post-class surveys will gauge students' knowledge levels, confidence, and satisfaction, while performance on quantitative assessments will measure their understanding of the material. The results from this year’s students will be compared against the results from the previous year, in which half of the data was collected from non-VR users. The comparison between this year’s fully VR students and the non-VR users from last year will uncover insights about the course’s effectiveness. This study continues the work on assessing VR use for aerospace education to inform future efforts and offer insights for educators considering adopting this technology.

Authors

Mollie Johnson Massachusetts Institute of Technology [biography]

Mollie Johnson is a graduate researcher in the Engineering Systems Laboratory at the Massachusetts Institute of Technology. She graduated from the Georgia Institute of Technology with a BS in aerospace engineering, and is furthering her education as a Master's student in AeroAstro at MIT.
Dr. Rea Lavi http://orcid.org/0000-0002-0788-7236 Massachusetts Institute of Technology [biography]

Rea Lavi received his Ph.D. degree from the Faculty of Education in Science and Technology, Technion—Israel Institute of Technology, Haifa, Israel. He is Lecturer and a Curriculum Designer with the NEET program, School of Engineering, Massachusetts Institute of Technology, Cambridge, MA, where he teaches thinking skills to undergraduate students. His research interests in STEM education involve the fostering and assessment of thinking skills involved in complex problem-solving, with special focus on systems thinking, creative thinking, and metacognition. His doctoral research received several awards, including the Zeff Fellowship for Excelling First-year Ph.D. Students and the Miriam and Aaron Gutwirth Fellowship for Excelling Ph.D. Students. Rea is also the inventor of the SNAP Method® for structured creative problem-solving (US & UK trademarks).
Dr. Olivier Ladislas de Weck http://orcid.org/0000-0001-6677-383X Massachusetts Institute of Technology [biography]

Olivier de Weck is a Professor of Aeronautics and Astronautics and Engineering Systems at MIT. His research focuses on the technological evolution of complex systems over time, both on Earth and in Space . He is a Fellow of INCOSE and ASEE and serves as Faculty Co-Director of the MIT Gordon Program
Luca Carlone Massachusetts Institute of Technology [biography]

Luca Carlone is the Boeing Career Development Associate Professor in the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology, and a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS). He received his PhD from the Polytechnic University of Turin in 2012. He joined LIDS as a postdoctoral associate (2015) and later as a Research Scientist (2016), after spending two years as a postdoctoral fellow at the Georgia Institute of Technology (2013-2015). His research interests include nonlinear estimation, numerical and distributed optimization, and probabilistic inference, applied to sensing, perception, and decision-making in single and multi-robot systems. His work includes seminal results on certifiably correct algorithms for localization and mapping, as well as approaches for visual-inertial navigation and distributed mapping. He is a recipient of the 2022 and the 2017 Transactions on Robotics King-Sun Fu Memorial Best Paper Award, the Best Student Paper Award at IROS 2021, the Best Paper Award in Robot Vision at ICRA 2020, a 2020 Honorable Mention from the IEEE Robotics and Automation Letters, a Track Best Paper award at the 2021 IEEE Aerospace Conference, the Best Paper Award at WAFR 2016, the Best Student Paper Award at the 2018 Symposium on VLSI Circuits, and he was best paper finalist at RSS 2015, RSS 2021, and WACV 2023. He is also a recipient of the AIAA Aeronautics and Astronautics Advising Award (2022), the NSF CAREER Award (2021), the RSS Early Career Award (2020), the Sloan Research Fellowship (2023), the Google Daydream Award (2019), the Amazon Research Award (2020, 2022), and the MIT AeroAstro Vickie Kerrebrock Faculty Award (2020). He is an IEEE senior member and an AIAA associate fellow.
Yun Chang Massachusetts Institute of Technology [biography]

Yun Chang received the B.S. degree in aerospace engineering and the M.S. degree in aeronautics and astronautics in 2019 and 2021, respectively, from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, where he is currently working toward the Ph.D. degree with the Department of Aeronautics and Astronautics and the Laboratory for Information and Decision Systems.
He is a member of the SPARK Lab, led by Prof. Luca Carlone. His research interests include robust localization and mapping with applications to multi-robot systems.
Mr. Chang is a recipient of the 2022 IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award, the MIT AeroAstro Andrew G. Morsa Memorial Award for demonstration of ingenuity and initiative in the application of computers to the field of Aeronautics in 2019, and the MIT AeroAstro Henry Webb Salisbury Award for academic performance in 2019.
Dr. Prabhat Hajela Rensselaer Polytechnic Institute [biography]

Prabhat Hajela is the Edward P. Hamilton Professor of Aerospace Engineering at Rensselaer Polytechnic Institute. He earned a Ph.D. in Aeronautics and Astronautics from Stanford University, and his research interests are at the intersection of multidisciplinary system design optimization and emergent computing approaches including evolutionary computing and machine learning. He has authored over 300 papers and articles and co-authored/edited 4 books on structural and multidisciplinary optimization. A recipient of the AIAA’s Biennial Multidisciplinary Design Optimization Award in 2004, Hajela is a Fellow of AIAA, ASME, and Aeronautical Society of India.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025