11–20 of 133 posts
Seniority is different from juniority in the ability to make things explicit as much as possible, from the requirements to the implementation specification.
I think in software engineering, the more explicit, the better.
IMO Tacit knowledge is what we used to call judgement. Judgement is basically knowing a bunch of things but having a good idea of which things are more important than others, and especially knowing which things are worth spending time on any which aren't. It's like when I see someone talking about financial options and they put everything on the board at once: what are puts and calls, what's an iron butterfly and oth…
The basic idea is this:
1. Deliberate practice only works for skills with a history of good pedagogical development. If no such pedagogical development exists, you can’t do DP. Source: read Peak, or any of Ericsson’s original papers. Don’t read third party or popsci accounts of DP.
2. Once you realise this, then the next question you should ask is how can you learn effectively in a skill domain where no good pedagogical development exists? Well, it turns out a) the US military wanted answers to exactly this question, and b) a good subsection of the expertise research community wondered exactly the same thing.
3. The trick is this: use cognitive task analysis to extract tacit knowledge from the heads of existing experts. These experts built their expertise through trial and error and luck, not DP. But you can extract their knowledge as a shortcut. After this, you use the extracted tacit knowledge to create a case library of simulations. Sort the simulations according to difficulty to use as training programs. Don’t bother with DP — the pedagogical development necessary for DP to be successful simply takes too long.
Broadly speaking, DP and tacit knowledge extraction represent two different takes on expertise acquisition. For an overview of this, read the Oxford Handbook of Expertise and compare against the Cambridge Handbook of Expertise. The former represents the tacit knowledge extraction approach; the latter represents the DP approach. Both are legitimate approaches, but one is more tractable when you find yourself in a domain with underdeveloped training methods (like most of the skill domains necessary for success in one’s career).
As an additional corollary, the tacit knowledge concept is a good argument against decision frameworks generally, which destroy information by trying to capture experience in a rubric.
[0] Getting more out of experts by focusing on results and not process: observations of people and neural networks http://marble.onl/managing_ml.html
Readers who are interested in the actionable aspects of this topic should probably read the last instalment in this series: https://commoncog.com/blog/accelerated-expertise/ The basic idea is this: 1. Deliberate practice only works for skills with a history of good pedagogical development. If no such pedagogical development exists, you can’t do DP. Source: read Peak, or any of Ericsson’s original papers. Don’t read t…
I think, by applying some of the core principles (variety of scenarios, high difficulty, guidance from expert available, high density of lessons, etc) I can learn things quicker, as well as help others learn things quicker. Even without CTA proper, which is its own skill I haven't taken the time to learn yet.
It is the same reason as you can't teach someone to play guitar by words without actually making them play and see the mistakes, even though you are perfectly capable to teach which area to press and how to strum and even make the person memorize the sequence.
Here are other examples I can think of:
- Learning programming in the first place. Many people struggle.
- Teaching rhythm to an older adult with no musical experience.
- Ear training. No explanation will substitute for practice.
This isn't to say that explanations never work and you shouldn't try, but rather their hit rate may be lower than you think, that coming up with the right exercises might work better, and that beta testing your work is important.
The strategic choice of how and what to study is also part of a good deliberate practice regime (interrupted from time to time in programming by needing to cram leetcode for no good reason, because why would a company want to hire somebody who was an expert at making modular easy-to-change systems when there are these heaps everywhere that need to be written from scratch in 15 minutes?)
Physicality and proximity are incredibly important, ironically maybe more so in the world of 'knowledge work' than when it comes to physical activity. An incredible amount of knowledge work happens implicitly when people organize spontaneously without them even being aware. Alex Pentland wrote an interesting book on it called Social Physics where he tried to empirically measure how much more effective in-person exchange of information is.