I read an interesting book titled Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt.
I found a section in the early chapter of this long book talking about the journey from novice to expert.
Here’s the brief opening taken from the book.
Once upon a time, two researchers (brothers) wanted to advance the state of the art in artificial intelligence. They wanted to write software that would learn and attain skills in the same manner that humans learn and gain skill (or prove that it couldn’t be done). To do that, they first had to study how humans learn.
They developed the Dreyfus model of skill acquisition, which outlines five discrete stages through which one must pass on the journey from novice to expert. We’ll take a look at this concept in depth; as it turns out, we’re not the first ones to use it effectively.
In the 1970s, the brothers Dreyfus (Hubert and Stuart) began doing their seminal research on how people attain and master skills.
The Dreyfus brothers looked at highly skilled practitioners, including commercial airline pilots and world-renowned chess masters. Their research showed that quite a bit changes as you move from novice to expert. You don’t just “know more” or gain skill. Instead, you experience fundamental differences in how you perceive the world, how you approach problem solving, and the mental models you form and use. How you go about acquiring new skills changes. External factors that help your performance—or hinder it—change as well.
Let’s start the journey.
The following are the five stages on the journey from novice to expert.
Stage 1. Novice
By definition, a novice is someone who has little or no previous experience in the corresponding skill area.
In this context, experience means specifically that doing the skill results in change of thinking on solving a certain problem. For instance, using a traditional for-loop-append-list in Python for 5 years to solve similar problems might not be counted as having 5 years experience. On the other hand, trying to apply another technique, such as list comprehension might change one’s understanding on how to speed up the computation process. Having tried various techniques improves one’s understanding in the corresponding area, and therefore considered as having experiences.
One of the characteristics that novices have is that they don’t particularly want to learn something new. They sometimes just care about accomplishing a goal instantly. Since they have zero to little experience, they sometimes don’t know what to do when encounter a problem.
To be able to overcome problems, novices need a guidance. The simplest example to this would be context-free rules. These rules have the form “Whenever X happens, do Y”.
However, these context-free rules can’t be considered as a collection of magical solutions. It’s not that easy to directly determine which rule to follow for a certain case. Moreover, additional explicit information are sometimes needed to make a certain rule clearer. This might throw a problem since we can’t constantly provide explicit definitions.
Novices need recipes
Stage 2. Advanced Beginners
To see the problem from a point of view of an advanced beginner, one must be able to break away from the fixed rules a little bit.
The keyword here is “a little bit” which means that advanced beginners are able to work on a problem by themselves, yet still have difficulty when looking for a right solution to a certain problem. This might happen since their experience is still not enough.
One of the characteristic of advanced beginners is that they want to get information fast. They don’t want to be bothered with fundamental concepts. Implicitly, they just want to apply the information without knowing what is inside the black box.
Another characteristic of advanced beginners is that they presume something that becomes the big picture of what they currently work on as irrelevant. This might be interpreted as they only focus on the specific context of the task they work on.
Advanced beginners don’t want the big picture
Stage 3. Competent
In this stage, one is already able to grasp enough understanding of a problem. They can use advices from experts effectively to troubleshoot problems by themselves and solve novel problems.
Competent practitioners don’t need fixed rules set. They try to understand the problem and then look for the relevant solutions. This is possible since competent practitioners already have enough past experiences on working on similar problems. However, when their experience is not enough, figuring out the solutions might still be difficult for them.
Their characteristic can be defined as “having initiative” and “being resourceful”. They can be a good mentor for the novices and don’t be a burden for the experts.
Competents can troubleshoot
Stage 4. Proficient
If advanced beginners presume “big picture” is irrelevant to their current job, proficient practitioners really need it. In other words, they want to grasp the understanding of the problem’s contexts before trying to solve it.
Proficient practitioners are also able to do self-improvement. Based on the mistakes they made, they can search for what caused them and try to not to repeat the same mistakes.
They are also able to improve their skills by learning effectively from others’ mistakes and reading case studies.
Having this self-improvement capability, proficient practitioners are able to apply what’s called as maxims. For simplicity, you could consider maxims as concepts that depend on the context. Therefore, maxims are something that can be adjust in accordance with the needs.
Proficient practitioners have enough experience to solve a certain problem. Using their experiences, they know what’s likely to happen next and when a solution doesn’t work. Therefore, they can select the appropriate solutions to a problem. In short, they really know what to do in the corresponding context.
Proficient practitioners can self-correct
Stage 5. Expert
Knowing what to do in a certain context is key to becoming an expert.
I’m going to cite the definition of experts from a book titled Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt:
“Experts are the primary sources of knowledge and information in any field. They are the ones who continually look for better methods and better ways of doing things. They have a vast body of experience that they can tap into and apply in just the right context. These are the folks who write the books, write the articles, and do the lecture circuit. These are the modern wizards.”
I really loved the above definition, by the way. What makes me amazed is that experts still have desire to share their knowledges and experiences even though there might be better methods and better ways of doing things. They don’t chase for perfection of their knowledge to start sharing their knowledges and experiences to others who are less experienced.
The primary characteristic of experts is that they work from intuition, not from reason. Even though they use intuition to build a solution, the interesting fact is that they genuinely don’t know how they came up with that solution. It just “felt right”.
Lots of experiences enable them to detect specific pattern in a problem and arrive at the relevant solution. Moreover, these experiences are also what make them able to separate irrelevant and very important information when looking for a solution.