A recent data error on the Student and Exchange Visitor Information System (SEVIS) website has thrown into doubt the number of international students in the US. The error, which spans an eight-month period from August 2024 to the present, has raised concerns about the reliability of federal datasets and the accuracy of recent reports on declining international student enrolments.
According to EnglishUSA, the error appears to show stagnating international student numbers, with flatlined totals for students on F and M visas. This contradicts expectations of natural enrolment shifts during this period. The error has cast doubt on recent headlines and media reports about declining international student enrolments in the US, which suggested an 11% decline between March 2024 and March 2025.
The US Department of Homeland Security (DHS), which runs SEVIS, was alerted to the error on April 14 and is working to resolve the issue. However, as of April 25, the dataset has not been updated, and DHS has not responded to requests for comment.
The error has raised concerns about the reliability of federal datasets, which are crucial for ensuring transparency in the system. Institutions and policymakers rely on these datasets to make informed decisions about international student enrolments and visa policies.
Despite the uncertainty caused by the data error, recent reports suggest that international student enrolment in the US has been growing. The Institute of International Education’s (IIE) fall snapshot reported a 3% rise in international student enrolment at the start of the 2024/25 academic year, building on sustained growth over the last three years.
The data error on the SEVIS website has cast doubt on the accuracy of international student enrolment figures in the US. While the error is being investigated, it remains to be seen how this will impact confidence in federal datasets and the international education sector. As the US government works to resolve the issue, institutions and policymakers will be closely monitoring the situation to ensure that accurate data informs decision-making.
