Range: How Generalists Triumph in a Specialized World

In the face of the unexpected, the range of available analogies helped determine who learned something new. In the lone lab that did not make any new findings during Dunbar’s project, everyone had similar and highly specialized backgrounds, and analogies were almost never used. “When all the members of the laboratory have the same knowledge at thei

In one instance, Dunbar actually saw two labs encounter the same experimental problem at around the same time. Proteins they wanted to measure would get stuck to a filter, which made them hard to analyze. One of the labs was entirely E. coli experts, and the other had scientists with chemistry, physics, biology, and genetics backgrounds, plus medic

Like math students, we need to be able to pick a strategy for problems we have never seen before. “In the life we lead today,” Gentner told me, “we need to be reminded of things that are only abstractly or relationally similar. And the more creative you want to be, the more important that is.”

Knowledge with enduring utility must be very flexible, composed of mental schemes that can be matched to new problems. The virtual naval officers in the air defense simulation and the math students who engaged in interleaved practice were learning to recognize deep structural commonalities in types of problems. They could not rely on the same type

Whether the task is mental or physical, interleaving improves the ability to match the right strategy to a problem. That happens to be a hallmark of expert problem solving. Whether chemists, physicists, or political scientists, the most successful problem solvers spend mental energy figuring out what type of problem they are facing before matching

but for knowledge to be flexible, it should be learned under varied conditions, an approach called varied or mixed practice, or, to researchers, “interleaving.” Interleaving has been shown to improve inductive reasoning. When presented with different examples mixed together, students learn to create abstract generalizations that allow them to apply

A similar study was conducted at Italy’s Bocconi University, on twelve hundred first-year students who were randomized into introductory course sections in management, economics, or law, and then the courses that followed them in a prescribed sequence over four years. It showed precisely the same pattern. Teachers who guided students to overachieve

The calculus professor who ranked dead last in deep learning out of the hundred studied—that is, his students underperformed in subsequent classes—was sixth in student evaluations, and seventh in student performance during his own class. Students evaluated their instructors based on how they performed on tests right now—a poor measure of how well t

As with the making-connections questions Richland studied, it is difficult to accept that the best learning road is slow, and that doing poorly now is essential for better performance later. It is so deeply counterintuitive that it fools the learners themselves, both about their own progress and their teachers’ skill.