Yale Professors Fight AI Impact: In-Person Meetings, Revised Policies
In response to the growing influence of AI tools like ChatGPT, some professors at prestigious institutions are introducing graded in-person meetings and revising course policies. Less than three years after its launch, ChatGPT has significantly impacted the field of computer science, prompting educators to reevaluate teaching methods.
Yale University's computer science department has seen professors implementing various strategies to combat AI use in their classrooms. Professor Alan Weide, for instance, has restructured his course 'Data Science and Programming Techniques' to make only in-person assignments directly impact students' grades. This shift aims to encourage personal effort and understanding, much like learning a new craft or training for long-distance running, as Professors Weide and others emphasize.
Professor Stephen Slade ensures in-class exams rely solely on students' memory and understanding by prohibiting access to ChatGPT and other resources. Meanwhile, Professor Ozan Erat's class disincentivizes AI use by making problem sets worth zero percent of the grade. However, specific information about the consequences of these actions and the use of generative AI tools in Yale's computer science courses is not widely available.
The computer science department lacks a unified policy on AI use, allowing professors to create individual course policies. Some professors report a decline in students' understanding of foundational concepts since the advent of ChatGPT. In response, the grade weights of problem sets in some courses have dropped to zero, while exam weights have increased to as high as 90 percent. Professor Rex Ying designs homework to make AI models not always correct and penalizes heavily for irresponsible use, further emphasizing the importance of personal understanding and effort in computer science education.
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