At a kitchen table somewhere in America, a seventh grader is doing her math homework. She works through a set of problems on paper, one by one, entering the answers into a computer program that instantly tells her whether those answers are correct. When she gets a problem wrong, the computer may offer a hint, it may explain the math behind the problem, or it may walk her through the problem, step by step (a process called scaffolding).
The next morning, when she takes her seat in class, her teacher has already viewed a report that shows how she and her 22 classmates did on the previous night’s work. Seeing that nearly everyone struggled with the same two problems, the teacher will take the time to discuss the underlying concepts of those problems before launching into a new lesson.
These scenarios may not seem revolutionary, but they represent a significant upgrade in the way middle-school math instruction has traditionally unfolded, with students completing homework largely unaware of whether their answers are right—or why they may be wrong—and teachers not fully tapped into what their charges have and have not mastered. The key difference for students and teachers is simple: feedback. When students get immediate feedback and help, they learn more. When teachers get feedback on the performance of the whole class, they can focus their efforts where it is most needed.
Providing immediate and constructive feedback is one of the guiding principles behind the learning platform that made those scenarios possible. Known as ASSISTments, it has been developed over the course of nearly two decades by a couple who first met when they were middle school teachers: Neil Heffernan, William Smith Dean’s Professor of Computer Science and director of WPI’s Learning Sciences and Technology program, and Cristina Heffernan, who directs the ASSISTments Foundation, a nonprofit formed in 2019 to scale up and expand the platform.