The proliferation of artificial intelligence in software engineering clearly has consequences for how to think about computing education.
[…] with GenAI, the production of code is no longer the bottleneck for students or professional engineers. Instead, the key challenges lie both before and after the production of code.
[…]
We must adapt our education mechanisms to address new metacognitive skills that are needed in a world with GenAI; curiosity, independence of thought, reading critically, and evaluating quality are paramount.
Computing Education When Writing Code Is No Longer the Challenge, by Ibrahim Albluwi, Dennis Bouvier, Claus Brabrand, Michelle Craig, Rodrigo Duran, Christopher Hundhausen, Colleen Lewis, Kevin Lin, Andrew Luxton-Reilly, Leo Porter, Karen Reid, David Smith, Claudia Szabo, Michel Wermelinger, Titus Winters, and Daniel Zingaro
There is the potential of students benefiting tremendously, if they “use GenAI as an ever-present and infinitely-patient tutor.” On the other hand, there is also the clear risk that they might “succumb to the temptation of unreflectively ‘outsourcing’ all effort to GenAI and submitting GenAI slop.”
Indeed.