Enrollment for 6.100A/L, 6.1010, and 6.1020 has declined since 2022-2023
Downward trend coincides with decline in Course 6-3 enrollment since 2022
Vivian Hir–The Tech
According to data obtained from the MIT subjects evaluation reports, enrollment for Electrical Engineering and Computer Science (Course 6) introductory programming classes—6.100A/L, Fundamentals of Programming (6.1010), and Software Construction (6.1020)—has decreased in the past three years following an overall increase from the 2017–2018 to 2022–2023 academic years. All three classes had peaked in enrollment in the 2022-2023 academic year.
As for the higher level programming classes, Software Design’s (6.1040) enrollment pattern was similar to that of the foundational programming classes, increasing from 64 in 2018–2019 to a high of 140 in 2022–2023, but fell in the last two academic years to a low 50. Meanwhile, Software Performance Engineering’s (6.1060) enrollment has hovered around 100 to 120 students across all years, except for the 2023–2024 academic year, in which 145 took the class.
The decrease in enrollment for 6.100A/L, 6.1010, and 6.1020 coincides with the recent decline of undergraduate enrollment in computer science and engineering (Course 6-3). According to enrollment data from the MIT Registrar’s office, the number of Course 6-3 students (including second majors) increased by 16.4% from 2016 to 2022, from 707 to 823. After a peak of 823 in 2022, however, enrollment has declined to 672, an 18.3% decrease.
One potential reason for the decline in Course 6-3 enrollment is the introduction of the artificial intelligence and decision making major (Course 6-4) in 2022, growing from 37 in 2022 to 372 in 2025, a tenfold increase. While Course 6-3 requires 6.1020, Course 6-4 does not, as the major focuses more on probability and statistics than software engineering.
Overall, Course 6 enrollment across all majors increased by 21% from 2016 to 2025. However, between 2024 and 2025, Course 6 enrollment declined for the first time in the last decade, from 1,672 students to 1,614, a 3.5% decrease. Previously, changes from year to year have always been positive, with the greatest increase being 7.2% from 2020 to 2021.
Other universities besides MIT are also experiencing declines in the number of students enrolled in computer science majors and classes. According to a 2025 article from The Atlantic, introductory computer science course enrollment at Duke University decreased by around 20% in the past year. At Princeton University, the number of computer science majors (juniors and seniors) declined by 20% in one year, from 135 in 2024 to 109 in 2025. Nationally, a preliminary fall report from the National Student Clearinghouse Research Center found that enrollment in computer and information science fields have decreased, from 5.8% for undergraduate two-year institutions to 15% for graduate schools.
More broadly, these downward trends reflect the trend of AI’s improvement at programming within the last few years. Nowadays, programmers can use AI coding tools such as GitHub Copilot to automate repetitive tasks, optimize code, and debug lines. Tools have even been developed to cheat at coding interviews successfully. In 2025, Columbia dropout Chungin Lee became famous for creating Interview Coder, an AI tool that helped him cheat in coding interviews and receive offers at companies such as Amazon.
In addition, the current job market is tough for computer science graduates, which may have influenced current college students to reconsider studying or majoring in computer science. According to a May 2025 report from Oxford Economics, employment for recent graduates ages 22–27 declined by 8% ever since 2022. As of February 2025, the unemployment rate for college graduates ages 22–27 who majored in computer science is 6.1%, according to the Federal Reserve of New York report. In general, the increased automation and efficiency that comes from AI has led to major tech companies such as Salesforce laying off thousands of workers. However, some critics believe that company executives are using AI automation as an excuse for other reasons, like adjustments in overhiring.
EECS Undergraduate Officer Katrina LaCurts SM ’10, PhD ’14, Senior Lecturer Ana Bell, and Principal Lecturer Max Goldman ’04, PhD ’12, did not respond to The Tech’s request for comment by the time of publication.