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My seven-year-old daughter came home from school a few days ago with an important message from her teacher. “Practice doesn’t actually make perfect,” she informed me. Mindless repetition, going through the motions, hurrying through exercises to get them done more quickly—none of this will help you master the intricacies of, say, getting the letter j to dip below the line and face in the right direction.

The same is true, of course, in other fields like music and sports. But figuring out how to practice better is tricky and has been the topic of long-running debates—think, for example, of the controversy around the concept of “deliberate practice” and . , from Mark Williams of the Institute of Human and Machine Cognition in Florida and Nicola Hodges of the University of British Columbia, digs into the intricacies of skill acquisition research to extract five key principles for coaches and athletes.

Balance Performance and Learning

Here’s one model of coaching: provide lots of detailed instruction with plenty of feedback, and focus on developing specific skills one at a time with repetitive drills. This will maximize short-term performance. The athletes will look good in practice. But if you want to maximize long-term learning instead, you should do the opposite: provide lower levels of instruction and feedback, and mix up different skills in unpredictable ways. Athletes won’t master the skills as quickly, but they’ll retain and build on them more effectively.

In the context of endurance training, there’s a similar trade-off between short-term performance and long-term fitness gains. A former training partner of mine used to quote Bob Kennedy, the former American 5,000-meter record holder, about how he knew he was getting fitter: the workouts didn’t necessarily get faster, he said, but they began to feel easier. The temptation to race workouts is an indication that you’re prioritizing immediate performance. Similarly, checking your watch every minute might help you nail the workout, but that frequent feedback might interfere with gradually learning to feel the right pace.

Choose Quality Over Quantity

Deliberate practice is a concept coined by the late Florida State psychologist Anders Ericsson, denoting practice that is systematic and effortful, targeting areas of weakness, and with appropriate feedback. Ericsson’s key point was that simply accumulating hours of practice doesn’t guarantee that you’ll keep getting better. The quality of your training matters as much as the quantity.

But figuring out the characteristics of high-quality training has proven to be more complex than Ericsson’s original definition, and remains an area of active research. In fact, I wrote a recent article on precisely that topic, drawing on new work by Norwegian sports scientist Thomas Haugen and his colleagues. Among the key concepts: the intention-execution gap. Harder or faster doesn’t always equate to better. What were your goals for the workout, and how close did you come to hitting them?

For motor skills, too, the most productive workouts tend to be neither too hard nor too easy. There may be some universal learning principles at work here: Williams and Hodges even cite from the computer science and machine learning literature that found an optimal error rate of about 15 percent to maximize the benefits of training.

Be Specific

“I loved the training; all we had to do was bayonet sacks full of straw,” Private Baldrick in the classic First World War-era British sitcom Blackadder Goes Forth. “I remember saying to my mum, ‘These sacks will be easy to outwit in a battle situation.’” Many an athlete has fallen into a similar trap, mastering the drills and challenges they’re assigned in practice only to discover that real-life competition is completely different. Even if your workouts superficially mimic competition—a basketball team that does nothing but scrimmage, for example—the anxiety and heightened intensity of a game change how you process information and execute movements.

That doesn’t mean that every workout should be a match or race simulation. But finding ways of simulating the challenges you’ll face can improve how well your training transfers to competition. Williams and Hodges suggest practicing skills in “highly variable and dynamic ways,” rather than repetitive and predictable drills. A favorite example from another former training partner of mine: his coach would occasionally halt an interval workout and have his runners sit on a bench for ten minutes, after they’d already warmed up and were about to start. Then, after the delay, they’d launch straight into the workout. This prepared them for the delays and disruptions that you inevitably encounter at races.

Foster Autonomy

The era of the coach as dictator isn’t over, but that athletes are no longer as willing to be bossed around. From a skill acquisition perspective, this makes sense. The scientific literature suggests that heavily prescriptive, hands-on coaching makes athletes less likely to retain what they’re learning. The goal, Williams and Hodges suggest, should be to nurture intrinsic motivation and self-guided discovery, providing the minimum amount of instruction and feedback necessary to stimulate positive change.

When I first started training seriously in high school, I did two interval workouts a week with my coach and his training group. For the rest of the week, the coach gave me some general guidance—I should run most days, keep the pace fairly relaxed, maybe see if I could get some of the runs up to an hour—but didn’t dictate the details. I’ve since trained with other coaches who specified weekly mileage targets, or even dictated the exact pace and distance of every run. But I always felt that early autonomy helped me develop as a runner, and is one of the reasons I’ve continued to enjoy running as an adult.

Respect Individual Differences

All the guidance above is based on the average group response to interventions in research studies. Most athletes pick up skills more effectively with low levels of instruction, high practice variability, and limited feedback. But there may be some individuals who thrive in the opposite conditions. And the context probably matters: novices may need more explicit instructions to learn certain skills correctly; elite athletes may need more detailed and nuanced feedback to perfect long-practiced moves.

And it’s not just about technical skills. People have different temperaments, different motivations, different personalities. A 15 percent failure rate may optimize learning for a computer, but it could nonetheless be too demoralizing for some humans, or too boringly easy for others. Coaches need to watch for these differences and respond to them, and those of us who coach ourselves need to find our own sweet spots.

A lot of this sounds like common sense, but the suggestion to limit instruction and feedback was unexpected. It seems like the opposite of what a good coach should do. It was interesting, though, how quickly examples of the “new” approach popped to mind from my own long-ago experiences as an athlete—like my former coach Matt Centrowitz Sr. making me take off my watch mid-interval and throw it in the grass so that I’d stop checking my splits so obsessively. Coaches and athletes have a lot to learn from scientists who study skill acquisition, but—as Williams and Hodges acknowledge in their conclusion—the learning goes both ways.

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