What do a precocious computer elf, a math-loving avatar, and a robot with terrible handwriting have in common? They’re all digitals spins on the educational theory of learning-by-teaching.
Decades of studies have shown that students learn a subject better when asked to help another learner. Traditionally, this meant taking the time to pair off students into peer-tutoring arrangements. Now, education researchers at about a dozen universities around the world are trying to supercharge the idea with technology. They’re creating virtual learners that need a human student to teach them everything from history to earth science.
Unlike real students, these “teachable agents” don’t get embarrassed or frustrated when they don’t know something. They respond reliably to good teaching without making random or silly mistakes, and their impact on learning can be precisely tracked and measured. Within a decade, teachable agents could be a classroom mainstay, researchers estimate. For now, most remain creatures of the lab, encountering real classrooms only in pilot studies.
While learning-by-teaching can be automated, the benefits are not automatic. Making a really effective digital learner isn’t simple.
“There’s not really just one reason why learning-by-teaching works so well,” said Daniel Schwartz, an education professor at Stanford who leads a lab developing teachable agents. “It’s a happy confluence of forces that help students learn. There’s a lot going on.”
For instance, having students teach pushes them to think about a topic’s underlying concepts and connections in order to gauge what another student knows and to build on that understanding. To boost this meta-cognitive effect, Schwartz and a team at Vanderbilt, led by electrical engineering and computer science professor Gautam Biswas, made a teachable agent for science lessons that would display every step of its thought process on screen as it learned. They called it Betty’s Brain.
© Stanford University, Stanford, California 94305.
