Rethinking the bad rap of rote

You know what gets a bad rap? Rote learning. Memorization. Repetition. In most classrooms, critical thinking smiles winningly and sets an apple on the teacher's desk while rote learning sulks in a corner facing the wall. The higher up the food chain, the less interested teachers seem to be in teaching by memorization. Even corporate trainers, who work in a realm where one would assume only outcomes matter, disdain this tried and true methodology. That's unfortunate, and here's why:

Automaticity. Researchers have found that automaticity, the ability to perform a task or recall a fact without thinking, is a key component of expertise. Benjamin Bloom went so far as to say that overtraining, practicing well beyond the level of competence, is the hallmark of excellence. He called automaticity "the hands and feet of genius." When you don't have to think about the basics anymore, your mind can concentrate on the finer points. The first time you drive on a highway you're just trying to stay alive. The ten-thousandth time you're only thinking about the fastest route home or the best way to get in front of the truck spewing blue smoke. That's expertise based on automaticity. And there's only one way to get automaticity, and that's through practice. Repetition. Doing something over and over until you can do it in your sleep. 

Expertise requires automaticity, and automaticity can be created through rote learning. So in essence, rote shortens the path to excellence. Why don't we take take the short-cut? It's not like this principle is lost to us. It's front and center in the most significant shift in our daily lives since the Internet: artificial intelligence. 

The way you teach a machine to think is by giving it hundreds of thousands of examples and then asking the software to do the same thing over and over while you assess the results and tweak the algorithms. In most cases, neural networks have to be trained on enormous amounts of data, doing millions of calculations over and over in order to learn. That's how we teach robots to think like humans. 

Above: "Teaching a robot to think," generated by AI

I know a lawyer who joined a new firm and was asked to give presentations to potential clients. He was required to memorize these presentations verbatim. As odd as it seemed at first, he became fluent in the main points of this new area of law almost overnight. From there he was able to dig deeper, to ask the right questions, to build on the foundation that was established by rote. That was speed to expertise. 

I led a training development project for a new venture in which front-line employees needed to interact with customers, and get up to speed very quickly. These employees were sourced and paid on the level of fast-food workers, but they weren't flipping burgers; they were dealing with people's nutritional health. We created five "mantras," short, simple, plain-language sentences that could be stated verbatim to customers. There was one for each of the five areas of expertise required: brand promise, nutrition, process, pricing, and product. Then each mantra had two "power phrases," which were slightly longer sentences that explained that mantra. It was one page of memorization that also served as the framework for all the other training to follow. We created short videos showing each mantra and each power phrase in action, to help with both memorization and delivery skills. We drilled and practiced. Voila. Speed to expertise via rote learning. 

It's funny how sometimes a big idea is an old idea with a new application. We have so many elearning tools that support, or could easily support, rote learning. Maybe we should think about why we teach machines the way we do, and draw some application from that. Maybe it's time for the old to become new again.