Recent developments in AI-generatedcode are merely the latest in a series of challenges to traditional computer science education. AI code generators, along with the plethora of available code on the Internet and sit...
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(纸本)9798400707896
Recent developments in AI-generatedcode are merely the latest in a series of challenges to traditional computer science education. AI code generators, along with the plethora of available code on the Internet and sites that facilitate contract cheating, are a striking contrast to the heroic notion of programmers toiling away to create artisanal code from whole cloth. We need not interpret this to mean that more, potentially automated, policing of student assignments is necessary: automated policing of student work is already fraught with complications and ethical concerns. We argue that instructors should instead reconsider assessment design in their pedagogy in light of recent developments, with a focus on how students build knowledge, practice skills, and develop processes. How can these new tools support students and the way they learn, and support the way that computer scientists will work in the years to come? This is an opportunity to revisit how computer science is taught, how it is assessed, how we think about and present academic integrity, and the role of the computer scientist in general.
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