MIT News: New algorithm aces university math course questions

Image: MIT News with figures from iStockphoto
Image: MIT News with figures from iStockphoto

by Adam Zewe | MIT News Office
August 3, 2022

Multivariable calculus, differential equations, linear algebra — topics that many MIT students can ace without breaking a sweat — have consistently stumped machine learning models. The best models have only been able to answer elementary or high school-level math questions, and they don’t always find the correct solutions.

Now, a multidisciplinary team of researchers from MIT and elsewhere, led by Iddo Drori, a lecturer in the MIT Department of Electrical Engineering and Computer Science (EECS), has used a neural network model to solve university-level math problems in a few seconds at a human level.

The model also automatically explains solutions and rapidly generates new problems in university math subjects. When the researchers showed these machine-generated questions to university students, the students were unable to tell whether the questions were generated by an algorithm or a human.

This work could be used to streamline content generation for courses, which could be especially useful in large residential courses and massive open online courses (MOOCs) that have thousands of students. The system could also be used as an automated tutor that shows students the steps involved in solving undergraduate math problems.

“We think this will improve higher education,” says Drori, the work’s lead author who is also an adjunct associate professor in the Department of Computer Science at Columbia University, and who will join the faculty at Boston University this summer. “It will help students improve, and it will help teachers create new content, and it could help increase the level of difficulty in some courses. It also allows us to build a graph of questions and courses, which helps us understand the relationship between courses and their pre-requisites, not just by historically contemplating them, but based on data.”

The work is a collaboration including students, researchers, and faculty at MIT, Columbia University, Harvard University, and the University of Waterloo. The senior author is Gilbert Strang, a professor of mathematics at MIT. The research appears this week in the Proceedings of the National Academy of Sciences.

Read more:
https://news.mit.edu/2022/machine-learning-university-math-0803