The esoteric world of pure math doesn’t usually play much of a role in promoting fairness in the U.S. political system, but Tufts mathematicians Moon Duchin and Mira Bernstein believe that needs to change. It is math, they say, that could help overcome gerrymandering—the practice of drawing legislative districts that favor one party, class or race.
A new artificial intelligence system designed at Tufts has made it faster and easier to learn to play the piano. Is it the future of education?
In a fourth-floor Tufts lab, a computer program was in the process of convincing a student that she was actually interacting with a human. It was spring 2015, and the student had come to the lab for a study involving a new way of teaching people to play the piano.
Yuksel and Oleson call their AI system Brain Automated Chorales, or BACh. It’s the first AI system to collect brain data and use that information to adapt a task for learners in real time. “It’s a huge deal,” said H. Chad Lane, an educational psychologist at the University of Illinois at Urbana-Champaign who studies intelligent technologies for learning. “No one has really successfully integrated neuroscience into interactive digital learning very well yet.”
With BACh’s flexibility, it becomes possible to envision brain-based AI tutoring systems that students could use in daily life—while doing homework, for example.
Despite a growing movement to glean insights from scholarly materials that are available online—from articles and data sets to conference presentations and lectures—one kind of academic document remains little examined. And that is the syllabus: a document that lays out the reading materials, topics and expectations of college courses. That, at least, was the case until January this year, when the Open Syllabus Explorer launched, integrating more than 1 million publicly available syllabuses and laying open their data in a conveniently searchable format.