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The reason most data scientists "remain junior" and why experience and skills are uncorrelated in the profession, is that most practitioners treat it as a "well structured profession" while it is "ill structured" noenthuda.com/2022/05/01/str new post based on

@ejames_c

's tweetstorm

noenthuda.com

Structures of professions and returns to experience

I’ve written here a few times about the concept of “returns to experience”. Basically, in some fields such as finance, the “returns to experience” is rather high. Irre…

Cedric Chin

@ejames_c

Replying to

@karthiks

Interestingly wickedness and ill-structuredness aren’t the same thing! The key feature of ill-structuredness is the variability of concept instantiation.

commoncog.com

Ill-Structured Domains Aren't Necessarily Wicked

Cognitive Flexibility Theory: the caveats. Also: a look at kind vs wicked learning domains, and what this tells us about building expertise in messy, real world domains.

3:18 PM · May 1, 2022Twitter Web App

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and

But that doesn’t detract from your main point: yes, data science careers are likely ill-structured.

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oh super. thanks. will read this.

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Actually I think the observation on ‘returns to experience’ is a great one. There’s an adjacent theory related to this, that explains why some people can reach mastery through experience (trial and error) and others cannot.

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Cedric Chin

@ejames_c

Aug 12, 2021

1/ Let's talk a little about how people learn in the real world. No, I'm not going to talk about classroom instruction, or pedagogical development, or enrolling in a cohort based course. None of that. Just a simple question: how do people ACTUALLY learn from doing?

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