Brown University economics professor Roberto Serrano experienced a 50% drop in scores for an in-person final after previously allowing take-home exams. The shift occurred following concerns about AI cheating among students, reflecting the mounting pressures students face in managing their academic workloads.
The issue began when Professor Roberto Serrano allowed take-home exams in response to a traumatic event on campus in December 2025, leading to an unprecedented enrollment for his ECON 1170 course.
Previously attracting few students, the course now had 86 enrolled, resulting in much higher average scores, including many perfect marks on the midterm exam.
In light of concerns over academic integrity and the potential for AI-generated cheating, Serrano switched back to in-person exams for the final.
This change resulted in the average score plummeting from 96 to 48, demonstrating the stark difference in student performance when not allowed to use AI assistance.
The situation raises significant questions about student ethics and the lengths they will go to in order to succeed under competitive pressures.
Despite capabilities, the reliance on generative AI tools can undermine actual learning, as evidenced by students' dramatic score drop when traditional assessment methods were reinstated.
This case illustrates the ongoing challenges of balancing technology use in education while maintaining academic integrity.
The phenomenon observed at Brown University may be a wake-up call for other institutions grappling with similar issues of AI cheating in examinations.
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Brown University economics professor Roberto Serrano experienced a 50% drop in scores for an in-person final after previously allowing take-home exams. The shift occurred following concerns about AI cheating among students, reflecting the mounting pressures students face in managing their academic workloads.