On this week’s Innovators podcast I spoke with Phil Long. He runs the newly-formed Center for Educational Innovation and Technology (CEIT) at the University of Queensland, in Australia. Phil is a transplant from MIT, where he was closely involved in the TEAL (technology-enhanced active learning) project. TEAL was the subject of a recent New York Times story: At MIT, Large Lectures are Going the Way of the Blackboard.
Born of John Belcher’s frustration that his large physics lectures were drawing fewer and fewer students each year, the TEAL experience mixes lecture segments with realtime interactive feedback (“clickers”) and guided teamwork.
Although the word technology is embedded in both TEAL and CEIT, it’s worth noting that sociology belongs there too. As Tim Fahlberg pointed out when I interviewed him about mathcasts and clickers, the technology that enables teachers to conduct realtime quizzes –and thereby adapt presentations on the fly — isn’t only about efficient measurement of what you could gauge roughly by a show of hands. The responses gathered by clickers are anonymous, and that makes all the difference. Nobody wants to raise a hand when asked: “Who didn’t understand that?”
Team formation is another area where technical and social engineering can usefully converge. If you test students before a course starts, Phil says, you can use that data to divide them into groups. But what heuristic should apply? He advocates teams of three drawn from the low-, middle-, and high-scoring groups. That arrangement encourages the most knowledgeable students to help teach their peers, and in so doing reinforce their own knowledge.
Phil points out that TEAL has so far been applied only in the domain of physics, where it has benefited from a wealth of research data about how students learn physics concepts. Part of CEIT’s mission will be to find ways to map the TEAL approach to other scientific domains, and also more broadly.