Key Takeaways
- Nearly 160,000 students took UNAM's entrance exam remotely using AI proctoring.
- Results showed a significant increase in top scores, leading to retakes for 58,000 students.
- The exam was conducted from late May through early June.
In an unprecedented move, nearly 160,000 applicants took the entrance exam for UNAM, Mexico's largest university, entirely remotely. The exam, which typically spans several weeks from late May to early June, utilized a 'lockdown' browser and AI-powered webcam proctoring software.
However, the results of this year’s exam were met with controversy, as they deviated significantly from previous years. Notably, between 2021 and 2025, only 3.5 percent of test takers scored a perfect 100 on the 120-question UNAM test. This year, an alarming 16.3 percent achieved this feat.
The discrepancy in scores has prompted UNAM to announce that over 58,000 students must retake the exam, raising questions about the reliability and fairness of the AI proctoring system used during the initial attempt.
UNAM officials have stated that they are investigating the irregularities, but have not yet provided a detailed explanation for the sudden increase in top scores. The university has assured candidates that their efforts will be supported throughout this process.
The decision to require retakes affects students who had hoped to secure places at one of Mexico's most prestigious institutions. Many are now facing additional stress and financial burdens as they prepare for another round of testing.
Critics argue that the AI proctoring system may have failed to accurately assess student performance, potentially due to technical issues or other unforeseen problems during the remote exam period.
UNAM has not disclosed any specific details about the technical challenges faced during the exam. However, it is understood that the university plans to conduct a thorough review of its AI proctoring system and possibly implement changes for future exams.
The incident highlights the complex challenges associated with administering large-scale remote examinations, particularly when relying on technology that may not be fully tested or reliable under all circumstances.
