Ultralearning Ch. 6 - Principle 3 - Directness

Go straight ahead.

The Importance of being Direct

Jaiswal’s story perfectly illustrates the third principle of ultra learning: directness. By seeing how architecture was actually being done and learning a set of skills that was closely related to the job position he wanted to perform, he was able to cut through the swaths of recent graduates with unimpressive portfolios.

Directness is the idea of learning being tied closely to the situation or context you want to use it in. In Jaiswal’s case, when he wanted to get enough architectural skill that firms would hire him, he opted to build a portfolio using the software those firms used and design in the style those firms practiced. There are many routes to self-education, but most of them aren’t very direct.

We want to work on collaborative, professional programs but mostly code scripts in isolation. We want to become great speakers, so we buy a book on communication, rather than practice presenting. In all these cases the problem is the same: directly learning the thing we want feels too uncomfortable, boring, or frustrating, so we settle for some book, lecture, or app, hoping it will eventually make us better at the real thing.

Directness is the hallmark of most ultra learning projects.

The opposite of this is the approach so often favored in more traditional classroom-style learning: studying facts, concepts, and skills in a way that is removed from how those things will eventually be applied: mastering formulas before you understand the problem they’re trying to solve; memorizing the vocabulary of a language because it’s written on a list, not because you want to use it; solving highly idealized problems that you’ll never see again after graduation.

Indirect approaches to learning, however, aren’t limited to traditional education. Many self-directed learners fall into the trap of indirect learning.

The easiest way to learn directly is to simply spend a lot of time doing the thing you want to become good at. If you want to learn a language, speak it. If you want to master making video games, then make them. If you want to pass a test, practice solving the kinds of problems that are likely to appear on it. This style of learning by doing won’t work for all projects. The “real” situation may be infrequent, difficult, or even impossible to create, and thus learning in a different environment is unavoidable.

The twin challenge of directness is that sometimes the exact situation in which you want to use the skill isn’t available for easy practice. Even if you can go straight into learning by doing, this approach is often more intense and uncomfortable than passively watching lecture videos or playing around with a fun app. If you don’t pay attention to directness, therefore, it’s very easy to slip into lousy learning strategies.

One of the big takeaways of Jaiswal’s story might not be the triumph of his self-directed learning project but the failure of his formal education.

I’m thinking that for my own education and ultra learning project, I need to be more direct. Throughout the OSSU courses though, I am doing the exercises, so that serves as practice to become a better programmer. However, if I want a specific job, I would need to directly learn the skills they are looking for. Granted, these OSSU fundamentals are building mental models that will be used on the job subconsciously or indirectly to help me solve problems, so I don’t think it’s a total waste, even though it may not seem directly transferrable. Later in the ultra learning journey, I can narrow in on a specific skillset. One I’m looking at is full stack engineering. I’ll get there eventually after going through the fundamentals of OSSU.

I need to get to the point of building apps and/or collaborating with others on professional programs, perhaps through open source. I’ll keep this idea of directness in mind.

Transfer: Education’s Dirty Secret

Transfer has been called the “Holy Grail of education.” It happens when you learn something in one context, say in a classroom, and are able to use it in another context, say in real life. Unfortunately, transfer has largely failed to occur in formal education, based on more than a century of intense work and research.

Other research showed that the ability to transfer was much narrower than most people had assumed.

Despite all this, the situation isn’t without hope. Although empirical work and educational institutions have often failed to demonstrate significant transfer, it is not the case that transfer doesn’t exist. Wilbert McKeachie, in reviewing the history of transfer, noted that “Transfer is paradoxical. When we want it, we do not get it. Yet it occurs all the time.” Whenever you use an analogy, you’re transferring knowledge. As Haskell pointed out, if transfer were really impossible, we would be unable to function.

Haskell suggests that transfer tends to be harder when our knowledge is more limited. As we develop more knowledge and skill in an area, they become more flexible and easier to apply outside the narrow contexts in which they were learned. I think might be related to the Matthew Effect. The more you learn, the better learner you become and the more you are able to apply knowledge.

The author. Has his own hypothesis as an explanation for the transfer problem: most formal learning is woefully indirect.

I think there can be an illusion of non transfer when it comes to technical subjects. The mental models built might not seem like they transfer at the time or even in the real world, but subconsciously they might be there playing a role.

I need to keep this idea in mind when writing reviews of courses. How can they potentially transfer to the real world?

Overcoming the problem of transfer with directness

Directness solves the problem of transfer. By learning in a real context, one also learns many of the hidden details and skills that are far more likely to transfer to a new real-life situation than from the artificial environment of a classroom. When we learn new things, we should always strive to tie them directly to the contexts we want to use them in.

Building knowledge outward from the kernel of a real situation is much better than the traditional strategy of learning something and hoping that we’ll be able to shift it into a real context at some undetermined future.

So should I start building out that desktop app idea? I was going for the traditional strategy which is to learn some core concepts formally, then start building, hoping that I’ll use that knowledge somehow there. But after reading this section, I’m thinking maybe I should start building out that idea, and learn outward from there whatever concepts may come up.

How Ultralearners Avoid the Problem of Transfer and Learn Directly

The simplest way to be direct is to learn by doing. Whenever possible, if you can spend a good portion of your learning time just doing the thing you want to get better at, the problem of directness will likely go away. If this isn’t possible, you may need to create an artificial project or environment to test your skills. What matters most here is that the cognitive features of the skill you’re trying to master and the way you practice it be substantially similar.

In other cases, what you’re trying to achieve may not be a practical skill. Many of the ultra learners whom the author encountered wanted, as their end goal, to understand a subject particularly well. The author’s own MIT Challenge was based around gaining a deep understanding of computer science, as opposed to a more practical goal of building an app or video game. Though this may seem like a case where directness no longer matters, that really isn’t true. It’s simply that the place you want to apply these ideas is less obvious and concrete.

In one case, a learner wanted to learn machine learning and artificial intelligence enough to where he could apply the skill of communicating these topics to others.

Although the findings of the research on transfer are fairly bleak, there is a glimmer of hope, which is that gaining a deeper knowledge of a subject will make it more flexible for future transfer and can be applied more broadly. This is the conclusion of Haskell, and although it doesn’t provide a short-term solution to the problem for new learners, it does suggest a path out for those who want to continue working on a subject until they master it.

This is good news for me, as someone who wants to deeply understand computer science, programming, and software engineering. I suppose I am on the right track by going through these courses and books instead of building apps.

How to Learn Directly

Learning directly is hard. It’s often more frustrating, challenging, and intense than reading a book or sitting through a lecture. But this very difficulty creates a potent source of competitive advantage for any would-be ultra learner. Let’s examine some of the tactics ultra learners use to maximize this principle and take advantage of the inadequacies of more typical schooling.

Tactic 1: Project-Based Learning

Many ultra learners opt for projects rather than classes to learn the skills they need. The rationale is simple: if you organize your learning around producing something, you’re guaranteed to at least learn how to produce that thing. If you take classes, you may spend a lot of time taking notes and reading but not achieve your goal.

Learning to program by creating your own computer game is a perfect example of project-based learning. Engineering, design, art, musical composition, carpentry, writing, and many other skills naturally lend themselves to projects that produce something at the end. However, an intellectual topic can also be the basis of a topic. For example, writing a thesis about military history.

I still want to build a desktop application, so I will do this in a future learning ultra learning project.

Tactic 2: Immersive Learning

Immersion is the process of surrounding yourself with the target environment in which the skill is practiced. Learning a language is the canonical example of where immersion works. Joining communities of people who are actively engaged in learning an also have a good impact, since it encourages constant exposure to new ideas and challenges. For example, novice programmers might join open-source projects to expose themselves to new coding challenges.

Tactic 3: The Flight Simulator Method

Simulating the environment is also a good approach. It’s the cognitive features of the environment, however, that matter. Flight simulator is a good example.

Tactic 4: The Overkill Approach

The overkill approach is to put yourself into an environment where the demands are going to be extremely high, so you’re unlikely to miss any important lessons or feedback. Despite the fears you may have, if you can get enough motivation to start this method, it’s often a lot easier to continue it long term.

One way you can overkill a project is to aim for a particular test, performance, or challenge that will be above the skill level you strictly require.

Learn Straight from the Source

Whenever you learn anything new, it’s a good habit to ask yourself where and how the knowledge will manifest itself. If you can answer that, you can then ask whether you’re doing anything to tie what you’re learning to that context. If you’re not, you need to tread carefully, as the problem of transfer may rear its ugly head.

The act of learning directly, however, is only half of the answer to the question of what you should do to learn well. Doing a lot of direct practice in the environment where you want to eventually use your skills is an important start. However, in order to master skills quickly, bulk practice isn’t enough. This brings us to our next principle of ultra learning: drill.