- Scott H Young - https://www.scotthyoung.com/blog -

Is it Better to Review Back or Learn Ahead?

I have a lot of open questions about learning. One of those is whether it is better to review back or learn ahead to maintain knowledge.

Reviewing back would be going through material you’ve already completed and testing yourself on it again. This is the principle through which spaced repetition systems work. I’m currently reviewing back words and sentences I learned in China through Anki [1].

Learning ahead means learning the next level as a means of strengthening knowledge. I took an introductory class in artificial intelligence during the MIT Challenge. Learning ahead would mean taking a more advanced AI course that builds on those concepts.

Advantages of Reviewing Back

The main advantage of review is that you get complete coverage. Learning ahead to more advanced material usually only builds on a subset of prior material.

During the MIT Challenge [2] I often did series of prerequisites: Single Variable Calculus -> Multivariable Calculus -> Differential Equations -> Signals and Systems. Each class used only some of the concepts from the prior class. Multivariable calculus introduced new concepts, but it didn’t stress some of the trigonometry identities of SVC. Signals and systems pretty much only considered transforms from differential equations.

Going back and reviewing means you cover all of those concepts, not just the ones used in a particular advanced course.

Advantages of Learning Ahead

Sometimes incomplete coverage is an advantage. The ideas that get reinforced in more advanced courses or projects tend to be the more important ones. If an idea is never reinforced in the future, it probably isn’t terribly important.

The main advantage of learning ahead, however, is that you learn new things and that can be more interesting than review. Learning new things is more motivating, and you’re expanding your knowledge rather than just reinforcing it. The idea of taking a more advanced course in AI is more appealing to me than the thought of going back and redoing old tests to make sure I remembered everything from three years ago.

The Inconsistency of Learning Ahead

When I did the MIT Challenge, my original plan was to use the learning ahead method [3] as the primary way I’d maintain my knowledge. I still think there are some obvious benefits of that approach, but I’m starting to see some drawbacks.

The biggest drawback, for me, is that learning ahead is less consistent than review. Review, whether it’s done through software like Anki, or through some kind of scheduled re-testing, can be set up to maintain the information consistently. That way, if you get busy and don’t have the time to push your knowledge in a particular area, you can at least be confident it won’t slip back.

I mentioned that, with this language challenge [4], I’m being more proactive about fighting forgetting. I’m scheduling regular review habits in advance, independent of any future study I do. That way I can maintain my ability even if I have long gaps where I don’t actively improve a language.

Although I’m a bit late, I’m also looking to do something similar for the MIT Challenge and my university education.

Obviously, maintaining all of the knowledge through review is unnecessary and time consuming. Academic knowledge is delivered in large swaths, not all of which will be particularly useful or interesting to you. However, going back and selecting out the specific concepts and skills I want to maintain might not involve considerable long-term review work to maintain. Perhaps several hours every few months?

Sometimes it’s Good to Forget

The truth is much of what we learn we’ll eventually forget at some point, or it will be buried so deep that it doesn’t come up easily in the right contexts. Learning is, even when done well, adding water to a leaky bucket.

However, if you develop systems for learning ahead or reviewing back to preserve the minority of knowledge that is important to you, the knowledge that stays in the bucket will be the kind that matters to you.