Neil Heffernan was listening to his fiancée, Cristina Lindquist, tutor one of her students in mathematics when he had an idea. Heffernan was a graduate student in computer science, and by this point — the summer of 1997 — he had been working for two years with researchers at Carnegie Mellon University on developing computer software to help students improve their skills. But he had come to believe that the programs did little to assist their users. They were built on elaborate theories of the student mind — attempts to simulate the learning brain. Then it dawned on him: what was missing from the programs was the interventions teachers made to promote and accelerate learning. Why not model a computer program on a human tutor like Lindquist?

Over the next few months, Heffernan videotaped Lindquist, who taught math to middle-school students, as she tutored, transcribing the sessions word for word, hoping to isolate what made her a successful teacher. A look at the transcripts suggests the difficulties he faced. Lindquist’s tutoring sessions were highly interactive: a single hour might contain more than 400 lines of dialogue. She asked lots of questions and probed her student’s answers. She came up with examples based on the student’s own experiences. She began sentences, and her student completed them. Their dialogue was anything but formulaic.

via How Computerized Tutors Are Learning to Teach Humans – NYTimes.com.