It is what it sounds like—leaving time between practice sessions for the same material. You might call it deliberate not-practicing between bouts of deliberate practice. “There’s a limit to how long you should wait,” Kornell told me, “but it’s longer than people think. It could be anything, studying foreign language vocabulary or learning how to fly a plane, the harder it is, the more you learn.” Space between practice sessions creates the hardness that enhances learning. One study separated Spanish vocabulary learners into two groups—a group that learned the vocab and then was tested on it the same day, and a second that learned the vocab but was tested on it a month later. Eight years later, with no studying in the interim, the latter group retained 250 percent more. For a given amount of Spanish study, spacing made learning more productive by making it easy to make it hard.
It does not take nearly that long to see the spacing effect. Iowa State researchers read people lists of words, and then asked for each list to be recited back either right away, after fifteen seconds of rehearsal, or after fifteen seconds of doing very simple math problems that prevented rehearsal. The subjects who were allowed to reproduce the lists right after hearing them did the best. Those who had fifteen seconds to rehearse before reciting came in second. The group distracted with math problems finished last. Later, when everyone thought they were finished, they were all surprised with a pop quiz: write down every word you can recall from the lists. Suddenly, the worst group became the best. Short-term rehearsal gave purely short-term benefits. Struggling to hold on to information and then recall it had helped the group distracted by math problems transfer the information from short-term to long-term memory. The group with more and immediate rehearsal opportunity recalled nearly nothing on the pop quiz. Repetition, it turned out, was less important than struggle.
It isn’t bad to get an answer right while studying. Progress just should not happen too quickly, unless the learner wants to end up like Oberon (or, worse, Macduff), with a knowledge mirage that evaporates when it matters most. As with excessive hint-giving, it will, as a group of psychologists put it, “produce misleadingly high levels of immediate mastery that will not survive the passage of substantial periods of time.” For a given amount of material, learning is most efficient in the long run when it is really inefficient in the short run. If you are doing too well when you test yourself, the simple antidote is to wait longer before practicing the same material again, so that the test will be more difficult when you do. Frustration is not a sign you are not learning, but ease is.
Platforms like Medium and LinkedIn are absolutely rife with posts about shiny new, unsupported learning hacks that lead to mind-blowingly rapid progress—from special dietary supplements and “brain-training” apps to audio cues meant to alter brain waves. In 2007, the U.S. Department of Education published a report by six scientists and an accomplished teacher who were asked to identify learning strategies that truly have scientific backing. Spacing, testing, and using making-connections questions were on the extremely short list. All three impair performance in the short term.
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. Demonstrating that required an extraordinarily unique study. One that only a setting like the U.S. Air Force Academy could provide.
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In return for full scholarships, cadets at the Air Force Academy commit to serve as military officers for a minimum of eight years after graduation.* They submit to a highly structured and rigorous academic program heavy on science and engineering. It includes a minimum of three math courses for every student.
Every year, an algorithm randomly assigns incoming cadets to sections of Calculus I, each with about twenty students. To examine the impact of professors, two economists compiled data on more than ten thousand cadets who had been randomly assigned to calculus sections taught by nearly a hundred professors over a decade. Every section used the exact same syllabus, the exact same exam, and the exact same post-course professor evaluation form for cadets to fill out.
After Calculus I, students were randomized again to Calculus II sections, again with the same syllabus and exam, and then again to more advanced math, science, and engineering courses. The economists confirmed that standardized test scores and high school grades were spread evenly across sections, so the instructors were facing similar challenges. The Academy even standardized test-grading procedures, so every student was evaluated in the same manner. “Potential ‘bleeding heart’ professors,” the economists wrote, “had no discretion to boost grades.” That was important, because they wanted to see what differences individual teachers made.
Unsurprisingly, there was a group of Calculus I professors whose instruction most strongly boosted student performance on the Calculus I exam, and who got sterling student evaluation ratings. Another group of professors consistently added less to student performance on the exam, and students judged them more harshly in evaluations. But when the economists looked at another, longer-term measure of teacher value added—how those students did on subsequent math and engineering courses that required Calculus I as a prerequisite—the results were stunning. The Calculus I teachers who were the best at promoting student overachievement in their own class were somehow not great for their students in the long run. “Professors who excel at promoting contemporaneous student achievement,” the economists wrote, “on average, harm the subsequent performance of their students in more advanced classes.” What looked like a head start evaporated.
The economists suggested that the professors who caused short-term struggle but long-term gains were facilitating “deep learning” by making connections. They “broaden the curriculum and produce students with a deeper understanding of the material.” It also made their courses more difficult and frustrating, as evidenced by both the students’ lower Calculus I exam scores and their harsher evaluations of their instructors. And vice versa. 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 the teachers set them up for later development—so they gave the best marks to professors who provided them with the least long-term benefit. The economists concluded that students were actually selectively punishing the teachers who provided them the most long-term benefit. Tellingly, Calculus I students whose teachers had fewer qualifications and less experience did better in that class, while the students of more experienced and qualified teachers struggled in Calculus I but did better in subsequent courses.
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 overachievement in their own course were rated highly, and undermined student performance in the long run.