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UID:pretalx-scipy2025-XMC8KU@cfp.scipy.org
DTSTART;TZID=PST:20250709T152500
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DESCRIPTION:Generative Artificial Intelligence (AI) is reshaping engineerin
 g education by\noffering students new ways to engage with complex concepts
  and content. Ethical\nconcerns including bias\, intellectual property\, a
 nd plagiarism make Generative AI\na controversial educational tool. Overre
 liance on AI may also lead to academic\nintegrity issues\, necessitating c
 lear student codes of conduct that define acceptable\nuse. As educators we
  should carefully design learning objectives to align with\ntransferrable 
 career skills in our fields. By practicing backward design with a\nfocus o
 n career-readiness skills\, we can incorporate useful prompt engineering\,
 \nrapid prototyping\, and critical reasoning skills that incorporate gener
 ative AI.\nEngineering students want to develop essential career skills su
 ch as critical\nthinking\, communication\, and technology. This talk will 
 focus on case studies for\nusing generative AI and rapid prototyping for s
 cientific computing in engineering\ncourses for physics\, programming\, an
 d technical writing. These courses include\nassignments and reading exampl
 es using NumPy\, SciPy\, Pandas\, etc. in Jupyter\nnotebooks. Embracing ge
 nerative AI tools has helped students compare\, evaluate\,\nand discuss wo
 rk that was inaccessible before generative AI. This talk explores\nstrateg
 ies for using AI in engineering education while accomplishing learning\nob
 jectives and giving students opportunities to practice career readiness sk
 ills.
DTSTAMP:20260607T104918Z
LOCATION:Room 318
SUMMARY:Generative AI in Engineering Education: A Tool for Learning\, Not a
  Replacement for Skills - Ryan C Cooper
URL:https://cfp.scipy.org/scipy2025/talk/XMC8KU/
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