Of course most people can be claimed to know how to ride a bike. The proof is simple: give them a bike and watch them without instructions mount onto it and take a ride without falling of – even in tricky conditions such as bumps or on slippery surface. However, the notion of “knowledge” is a little bit trickier than that, and a too “binary” notion of knowledge hurt us.
For example, take anyone of those that “know” how to ride a bike, and ask them to explain how to make a left turn. Chances are high, that you either will get no answer at all, or an answer that if followed will make you fall over - which in a pragmatic sense can be judged to be “wrong” or at least “incorrect” (did not cause the desired effect).
In the same way I can ask about myself: do I know “Java exceptions”, “EJB 3”, “agile system development” or “project management”? And when reading CVs I am regularly frustrated over just being given a long list of acronyms and frameworks; a list that tells me nothing about whether this person has been to a one-day class on Hibernate, or if she can wrinkle out modelling mistakes that will hurt performance.
For my own use I like to view knowledge not as binary (“know” vs “not know”), but rather as having levels of “depth of knowledge”. A main source of inspiration is Benjamin Bloom’s taxonomy. He defined six levels of “cognitive learning” (knowledge, comprehension, application, analysis, synthesis, and evaluation).
However, when applying this to system development, I usually collapse the three deepest levels (analysis, synthesis, and evaluation) to one, ending up with four levels. The reason for doing this is that I seldom see the need to distinguish between the deepest three, but often want to point out the difference between the first three (knowledge, comprehension, and analysis) in relation to the four latter stages. I guess a cynic might point out the choice of collapse as an observation of the state of our industry.
One thing I really like with Bloom’s taxonomy is its focus on utilisation of the knowledge. It quantifies by measured in the abilities to process and use information in a meaningful way, simply by telling what you can do at a given level. Note here “utilisation” and “measure” – two words that strongly align with my affection for pragmatism in software development.
With each level there are a couple of typical verbs attached – things a person is supposed to be able to do at that level. And this gives something that is measurable in a testable fashion.
So, the four levels I use with some typical verbs are
- Recognition (renamed: originally “knowledge”): recite, list, label, locate
- Comprehension: restate, give example, summarise
- Application: apply, solve, show
- Analysis (including Synthesis and Evaluation): compare, compose, invent, critique, evaluate, judge
Let me apply these levels to myself and some areas of knowledge just as examples.
So, do I know the Java memory model? Well, I follow along when my colleague Tommy talks about it, but I am not sure I could restate it without serious mistakes; so at recognition level yes, and perhaps at comprehension level, but not deeper.
Do I know Scrum, Java exceptions, or Domain Driven Design? Hey – how long do you want me to talk about it? I guess I could spend endless hours in discussion on those topics with other experts – so I would say analysis level knowledge.
Do I know JPA 2.0? Sure, I could solve a problem by using it, but I would probably fail when people start discussing trade-offs and what is happening “under the hood” in different implementation; in other words application level knowledge.
As a side note I would say the levels are logarithmical (like the Richter Scale), so that each level of depth takes ten times amount of thoughtful experience to reach, compared to the previous. You can learn a buzzword by listening to a “sales-level” presentation of one hour. To be able to restate it yourself, you probably need to spend a day (10 h). Before you can practice it without checking up details all the time, you probably need two-to-three weeks experience (100 h). And the level where you can compare and contrast different approaches will probably take half a year (1000 h). Of course it is the two latest levels that are most interesting and important to system developers.
Back to the bike riding: recognition would be “yeah – bikes are a kind of vehicle – I see one over there!”; comprehension would be “you get onto it, pedal to get speed, steer by pulling the handles, and break by pedalling backwards”; application would be: “let me show you – watch me!”.
And analysis level? Well, if you want to turn left you should not pull the left grip – that will cause you to tip over to the right due to the centrifugal force you expire when the bike starts turning left. In short – the bike will turn left, but you and your centre of gravity will continue forward; so you fall into the ground on the right hand side of the bike.
And, by the way: centrifugal forces do exist.
To actually turn left you first pull the right handle. The effect is that you start falling over to the left. After a split of a second you have fallen the appropriate amount so that your angle towards the ground will make gravity and centrifugal force balance for the turn you intended. Then, you pull the left handle to actually do the left turn. And as you now have the appropriate angle, forces balance out and you stay on top. People trying to explain this often express it as doing a small “contra-turn” in the opposite direction as a preparation before making the “real” turn.
If you want to see this in action, have a friend film you while just doing some cycling around on the backyard, and then watch it frame by frame. You will see that you intuitively do the right thing – but you probably had no idea you did.
Note that for most of us there is no need for analysis level knowledge on bicycling – we are perfectly happy to just be able to ride that bike. The analysis level knowledge of bike riding you find at people like motorcycle driving instructors or those that just have studied a little bit too much analytical mechanics.
The same goes with people in the system development field. Just doing stuff and gaining “experience” does not give analysis level knowledge. To there you also have to have an analytical process in place that constantly evaluates what you do, why you do it, and what the alternatives could be.
Culture that analytical process.
Most people do not know how to ride a bike – they simply do it.