Productivity

Dreyfus Model for Skill Acquisition: From Novice to Expert

Dreyfus Model

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Acquiring new skills and honing them over time is iterative. You have to keep referring back to see how you can improve and get better. Self-Assessment is a must-have component to acquiring and honing a skill. The Dreyfus Model identifies five stages of skill acquisition which can give you a good insight into assessing where you stand. Put forth by Stuart E Dreyfus and Hubert E Dreyfus in 1980, The Dreyfus Model can still be used today. A summary of the paper was published by Stuart E Dreyfus in 2004.

Dreyfus Model for Skill Acquisition: Quick Look

What is the Dreyfus Model?

According to The Dreyfus Model, when learning a new skill, you pass through five stages of development.

  1. Novice
  2. Advanced Beginner
  3. Competence
  4. Proficiency
  5. Expertise

In the 2004 paper, each stage mentioned above is summarized with respect to four categories: Components, Perspective, Decision, and Commitment. A lot of the traits highlighted in the Dreyfus Model also correspond to having a millionaire mindset.

Let’s define these four terms to better understand the different developmental stages and the categories.

Components: These are the elements that can be perceived by the learner which can be context-free or situational. Situational refers to the situation the learner is in.

Perspective: The ability of the learner to pick a component to focus on.

Decision: The decisions the learner makes in a particular situation. Decisions can stem from analytical analyses based on the information the learner has. The decisions can also be made intuitively which comes with experience.

Commitment: The extent to which the learner is immersed in the learning situation. It can either be detached or involved.

Five Stages of Skill Acquisition

Let’s take a closer look at the five stages with respect to the four categories mentioned above.

1. Novice

As a novice, you have little or no previous experience to show in the situation. You can, however, recognize some elements without any context. To start out, you follow a prescribed set of rules which are not necessarily all-encompassing.
Python Novice

If you are a novice and want to learn Python, your context-free features would include knowing the basics of operating a computer, downloading and installing files, and basic math operations. Initially, you will work your way around with the basic rules you are given: printing a statement (Hello World!), performing basic math operations, logical operators like and/or, loops, etc.

Since these rules will not give you a complete picture, you will tend to make mistakes. Even though you know of the rules, as a novice, you lack the ability to recognize the context of the rules in the situation. You make decisions analytically (based on the rules you have been given) and you are not completely involved in the learning process at this point. You will get stuck in many infinite loops until you move on to the next stage.

2. Advanced Beginner

You have learned the basic rules and from your mistakes made as a novice which would make you an Advanced Beginner.

You have a better understanding of the situation you need your skills for. Up until now, you have been introduced to some real-world situations and you try applying your newly learned skills in new situations.
Python Advanced Beginner

Extending the example of learning Python, now you have worked on enough things to know when to use a for loop and when to use a while loop. You have a better idea of what would lead you into an infinite loop when writing code and about indenting your code. You would still make mistakes but you are moving more towards autonomy.

Your learning can be done in a detached frame of mind with analytical decision-making based on the instructions you have been given.

3. Competence

At this stage, you have been introduced to a lot of procedures and rules which feel overwhelming. To add to this, you lack the ability to clearly know where each rule needs to be applied.

As a competent learner, you can only choose a plan for a situation without knowing fully if it would work. This stage can result in overwhelm and also bring about satisfaction after pulling off a seemingly huge feat.
Python Competent

When learning Python, you would not have a clear idea of whether to use a try-except block or if-else conditions. You could be using Python to automate tasks using an API which would require you to know how to iterate over the data you get and understand JSON which can seem overwhelming. But it can also result in a huge sense of achievement once you have successfully automated a few tasks.

Your decision-making is still analytical like before but you are on your way to making your own decisions. You choose to make decisions in the face of uncertainty which gives you a good insight into how to improve from your mistakes. Making mistakes and learning from them is also essential to having a millionaire mindset. Because you are more emotionally involved in the task which makes it tough to have a detached learning process like before.

4. Proficiency

All the experience gained through different tasks and real-world applications adds to gaining a lot more in-depth knowledge.

When you are proficient, you have learned from your mistakes in the past and had successes to boost your confidence. This is the point where your approach shifts from a rule-based one like before to a more situational-based one.
Python Proficient

Once you have worked on some Python projects, you also know the most efficient way to write code. You make sure you are following the DRY (Don’t Repeat Yourself) principle to make future changes easier. If you are learning Web Development with Python using Django or Flask, you also recognize best practices in terms of website loading time and making database queries efficiently.

Being proficient, you not only know the potential ways you could tackle a situation, but you also learn to recognize the best way. Your emotional involvement in decision-making makes your learning a lot more involved than before. You still operate analytically based on some set rules but you are inching closer to autonomy.

5. Expertise

You have gained a lot of in-depth know-how on the situation and how to optimally handle things. Compared to a proficient individual, the expert is capable of making more refined judgments on how to achieve a goal. The expert has a vast number of skills and knowledge of real-world situations.

An individual with expertise in Python would be able to better recognize what is wrong with a code block. They would also know the best ways to fix the code and make it more efficient. The thinking time when pondering over code is mostly short in the case of an expert even in unfamiliar situations.

At the Expertise stage, your decision-making is intuitive than rule-based as seen earlier. You are also more experienced and more involved in learning.

How to Apply The Dreyfus Model?

Going from a novice to an advanced beginner and then all the way to becoming an expert takes time. Contributing meaningfully to your field involves a learning curve. It also depends on your major or area of interest. A surgeon might take longer to go from one stage to the next, while some other professional would not take as long. But at its core, you can still use the Dreyfus Model to assess where you stand and hone your skills based on your inner scorecard.

Using learning techniques like spacing, retrieval, interleaved practice, and active reading can help you gain expertise. It is especially important to evaluate where you are in the five stages because of the Dunning-Kruger Effect.

Dunning-Kruger Effect and Dreyfus Model

The Dunning-Kruger Effect was proposed by David Dunning and Justin Kruger in 1999. It is a cognitive bias in which unskilled individuals overestimate their knowledge or ability. Unskilled individuals tend to make the wrong choices based on wrong conclusions and incompetence. Their lack of knowledge prevents them from realizing their pitfalls. The 1999 paper found improving the skills of the individuals helps them see their limitations.

The Dreyfus Model could be a helpful model for self-evaluation and negating the Dunning-Kruger Effect. Let’s look at two scenarios where this model is effective: learning in college and self-learning after college.

Using the Dreyfus Model in College

Students in college develop a tendency to go along with tests and forget the material soon after. Tests don’t go too deep when it comes to self-evaluation.

It is likely that the college course that you are taking is not going to take you to Proficiency or even Competence in terms of real-world applications. You could use the Dreyfus Model to figure out if you are a novice, an advanced beginner, or somewhere further. If you are a novice, how can you progress to becoming an advanced beginner? You might be following a set of rules from your professor, are you thinking about applying those rules to newer situations?

Applying the Dreyfus Model in your college courses can help you evaluate yourself beyond your test scores. It also positions you to learn and assimilate concepts you will learn in the future. By thinking in terms of the model, you are open to learning from your mistakes and also applying your knowledge to learn better.

Using The Dreyfus Model in Self-Learning After College

Learning beyond and after school is one of the driving motivations behind Learn Repeat Academy. When you are self-learning you might not have effective testing tools to assess your progress. You could have no background before you decide to learn Python, SQL, Machine Learning, or math. Different platforms like Udemy, Skillshare, or Coursera also have different learning processes. Let’s look at how you can make use of this model at every stage.

Novice

You can start out by looking for YouTube tutorials that go over the basics. Searching for something on YouTube is way too easy compared to reading a book or doing a complete course. If you can’t find proper videos on YouTube, you can pick up a book that gives you the bare bones of what you need to know. You could also look for an introductory course on any online platform that requires little to no prerequisites. If you are interested in learning Python, you could look through the numerous free Python tutorials on YouTube to start, or look for a Python Bootcamp. You could also take a look at the following books to start learning Python:

  1. Python Crash Course by Eric Matthes
  2. Head First Python by Paul Barry
  3. Learn Python 3 The Hard Way by Zed Shaw

Advanced Beginner

Now that you have familiarized yourself with the basics, you need to explore more to see what is out there to learn. You might stumble upon new areas that need additional rules and instructions. If you start learning Python, you could gravitate towards Data Science, Machine Learning, or even Web Development. You can seek additional resources like online courses or books to explore these topics.

  1. Python Data Science Handbook by Jake VanderPlas
  2. Introduction to Machine Learning with Python by Andreas C Muller and Sarah Guido
  3. Flask Web Development by Miguel Grinberg
  4. Django for Beginners by William Vincent

Get a full list of books to learn Python here.

Competence

This might be the most challenging stage stemming from overwhelm and frustration. At this point you know the rules, you would make quite a few mistakes which you would have to learn from. People tend to give up at this stage but it is where you need to push yourself to progress. You would also be able to learn better by talking to people who are well-versed in what you are learning. This could be your boss, co-worker, friend, or even a certified instructor. When it comes to learning Python or any coding language, you would try to build something or work on projects to get acquainted with real-life applications.

Proficiency

You could progress further with a lot more hands-on activities/projects to become proficient. At this point, you are on your way to replacing your rule-based approach with a more situational one. After progressing from being competent, you are just iteratively refining yourself to polish your skill.

Expertise

Years of experience in working on your skill will get you to this stage. You would be a lot more intuitive when working on something. It is important to note that learning does not stop after achieving expertise. You would still need to learn and update your knowledge as and when new information comes your way.

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