Learning That Sticks: Principle × Practice × Review

What makes learning stick?

Learning sticks when you understand the principle underneath the tool, apply it to something real, and review what broke and what survived. I write this as a formula, learning that sticks = principle × practice × review, and I multiply the 3 factors because a zero in any one of them leaves the other 2 unable to hold the learning in place.

Most of us learn in a predictable way. We choose a field, collect courses, tutorials and documentation, and measure progress by how much material we have covered. Finishing lessons feels like progress, because every lesson finished produces a small sense of completion. The difficulty is that covering material and keeping it are different things, and the second is rarely checked.

Why does most learning fade?

Most learning fades because it stays at the level of recognition. A tutorial shows which button to press, and you press it. An explanation makes sense while you read it, and you agree. Access to explanations has become easier than ever, and AI can now explain almost any technical subject within seconds, so the gap between recognising an explanation and understanding the subject has become easier to overlook.

You discover that gap the first time the normal path stops working. The software changes, an interface is redesigned, the data contains something unexpected, or a tool that you learned is replaced by another. What remains of what you learned when the tool that carried it disappears? And how much of your knowledge was knowledge of the subject, and how much was knowledge of one interface?

The better approach is to treat learning as 3 separate acts, and to check that each one has happened.

What is the principle?

The principle is the idea that stays true when the tool changes. The principle answers the question of why the tool works the way it does, what assumptions it makes, where its dependencies are, how it can fail and how a result can be verified.

Take accounting as an example. The tools change, from paper ledgers to spreadsheets to cloud software, but the principle that every number needs a history, and that every difference is explainable, stays the same. A person who learned the principle can pick up a new accounting tool in a short time. A person who learned only the screens starts again each time.

Learning the principle is slower at the beginning, because it takes longer to understand how something works than to learn which buttons to press. The principle pays back later in flexibility, since the technology can change without taking the whole understanding with it.

What counts as practice?

Practice is applying the principle to something real, with real data, real users, incomplete information and conflicting requirements. A toy exercise teaches the exercise. A real task exposes the assumptions that a clean example hides.

Practice can be small, such as a spreadsheet system, a short script, a small automation, a reporting process or a piece of infrastructure that something real depends on. What matters is that the result is used, because an idea becomes much more useful once it has survived being used. My own work grew this way: spreadsheet systems and VBA tools built to remove repeated work led to scripts, to applications and eventually to databases, deployment and infrastructure, and each step showed me what I needed to study next.

What does review involve?

Review is checking, after the work is done, what broke and what survived. Review means comparing what you expected to happen with what did happen, writing the difference down, and adjusting the principle you were relying on.

Research on memory supports the value of checking yourself. In a 2006 study, Henry Roediger and Jeffrey Karpicke found that students who tested themselves on a passage remembered more of it a week later than students who simply read it again. The study concerned memory for text and not professional skill, but the same logic applies: recalling and checking strengthens understanding more than repeating exposure to the same material.

A practical review asks 3 questions. What did I expect, and what happened instead? Which part of my understanding was wrong? What would I do differently if I started again? Without these answers, practice repeats the same mistake with more confidence.

Why does learning need all 3 factors?

Learning needs all 3 factors because each factor covers a weakness that the other 2 cannot. Consider what happens when one is missing:

• Practice and review without a principle produce skill that is tied to one tool and breaks when the tool changes.
• Principle and review without practice produce confident explanations that have never met real conditions.
• Principle and practice without review produce experience that does not turn into improvement, because nothing was checked.

In every case, strength in 2 factors gives a false sense of progress. That is why I treat the formula as a product and not as a checklist where a good average is acceptable.

How can you apply this to what you are learning now?

You can apply it in 3 steps, using one skill that you are learning at the moment:

1. Write down the principle behind the tool in one or two sentences, and note what would still be true if the tool were replaced.
2. Build one small thing that someone or something real depends on, and use it under real conditions.
3. Review the result a week later by writing down what you expected, what happened, and what the difference shows you about your understanding.

If you cannot complete the first step, the next thing to study is the principle. If you cannot complete the second, the next thing to do is build something. If you cannot complete the third, the learning is not yet secure, however much has been covered. Treat the missing step as the plan for the next week, because it is where the learning is currently weakest.