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Aerospace Engineering Education in the Era of Generative AI

Conference Session
Aerospace Division (AERO) Technical Session 4 - Teaching Methodology
Collection
2025 ASEE Annual Conference & Exposition
Authors
Julie B. Coder, The Pennsylvania State University; James G Coder, Pennsylvania State University; Mark D. Maughmer, The Pennsylvania State University
Tagged Divisions
Aerospace Division (AERO)
applied aerodynamics and aircraft design. ©American Society for Engineering Education, 2025 Aerospace Engineering Education in the Era of Generative AIAbstractThe proliferation of large-language model (LLM) generative artificial intelligence (AI) tools likeChatGPT raises an inevitable question of how it should impact student assessments in aerospaceengineering. To evaluate this, a large sample of multiple-choice questions from undergraduateaerodynamics and aeronautics courses were input into ChatGPT-4 and Gemini and the accuracyevaluated. The cognitive level of each question was coded using Bloom’s taxonomy based onconsensus of the authors. It was found that that generative AI performs increasingly poorly as
Relevance Score: 0.3258348

Student Rocketry: Out-of-Class Learning Experiences from a Year-Long Capstone Project at University

Conference Session
Aerospace Division (AERO) Technical Session 4
Collection
2024 ASEE Annual Conference & Exposition
Authors
Tim Drake, Saint Louis University; Srikanth Gururajan, Saint Louis University
Tagged Divisions
Aerospace Division (AERO)
) classes, they are taught from the perspective of developingand executing algorithms, and there are no classes to teach the actual building of a computingcluster. This is another prime example of our need to learn outside the classroom to accomplishour goals. As most students do, we turned to Artificial Intelligence (AI)/ChatGPT [6] for help – tobe used as an interpreter or editor rather than a coder.Following a tutorial from a website [10], I learned the basics of setting up a multiple-node clusteron Ubuntu. I checked that each PC had adequate RAM, a hard drive, and a simple graphics card.The cluster hardware consists of 20 desktops, each with an Intel i7-4790 quad-core 3.60 GHzprocessor and 16GB of RAM, running Ubuntu 22.04.3 LTS connected to a
Relevance Score: 0.14266424