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- Multidisciplinary Engineering Division (MULTI) Technical Session 7
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- 2023 ASEE Annual Conference & Exposition
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Robert L. Avanzato, Pennsylvania State University, Abington
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Multidisciplinary Engineering Division (MULTI)
includegenerative AI models such as the text-to-text model, chatGPT [9], GPT-4 [9], and others. LLMsuse a transformer model architecture instead of a CNN and the transformer architectures arecurrently being explored for use in computer vision applications. Models such as chatGPT (andothers) have also proven useful for programming code generation and productivity enhancement.These LLMs are of growing importance but are outside the scope of this project and paper.2. Deep Learning Curriculum and ProjectsThe specific goal of this project is to design and implement an instructional 7-week coursemodule to introduce deep learning and computer vision with a project-based orientation. Asmentioned, the target course is a senior-level engineering design course in
- Conference Session
- Multidisciplinary Engineering Division (MULTI) Technical Session 3
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- 2023 ASEE Annual Conference & Exposition
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Angela R. Bielefeldt, University of Colorado, Boulder
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Multidisciplinary Engineering Division (MULTI)
degrees that werebenchmarked in more detail, 19 ‘engineering’ and ‘general engineering’ degrees required a lowerpercentage of technical coursework and offered a lower percentage of curricular choicecompared to 7 degrees that included the word interdisciplinary, integrated, or multidisciplinary intheir name. A few programs require students to take the NCEES Fundamentals of Engineering(FE) exam prior to graduation. The AI-based program ChatGPT definitions of general,interdisciplinary, and integrated all emphasized breadth, multiple disciplines, and design, whilealso including the distinguishing factors of practical (for general) versus complex and innovative/novel (interdisciplinary and integrated), and the importance of social impacts (integrated
- Conference Session
- Multidisciplinary Engineering Division (MULTI) Technical Session 6
- Collection
- 2023 ASEE Annual Conference & Exposition
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Darcie Christensen, Minnesota State University, Mankato; Lauren Singelmann, Minnesota State University, Mankato; Rob Sleezer, Virginia Tech; Emilie A. Siverling, Minnesota State University, Mankato
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Diversity
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Multidisciplinary Engineering Division (MULTI)
more learner-centered and focusedon formative feedback rather than summative evaluation [1].As the world of technology continues to advance, a shift and embracement of new assessmentmethods is appropriate and necessary. For example, as of early 2022, the New York Timesreported that universities are now having to change the way they are teaching and assessingstudents because of the widespread availability of A.I. Chatbots such as ChatGPT [12]. WithinIE at Minnesota State University, Mankato, differential methods of assessment have beenemployed for over a decade and we want to share our experiences with oral exams to supportothers in embracing the changing world, better preparing engineering students for their futurepositions.Overview of