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Design Thinking Books (2024)

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Re: Design Thinking Books (2024)

#61

Post by [deleted] »

jbs789 wrote: post #53
yakkomajuri wrote: post #12

I'm a dev and recently picked up "The Design of Everyday Things" as an attempt to become more design-oriented. Everyone raves about this being like the bible of design. So far I'm about 80 pages in and have found it extremely academic and not very practical, sometimes deriving conclusions that are so far from reality that they are a bit concerning, like how a strong password does not matter because once they inevitab…

The Norman door was a powerful example for me, as it emphasises that the user is not the problem but the push door with the handle is the problem. And if you’re designing the door, it is your responsibility to think deeply and observe behaviour, to design an intuitive interface. I do agree that it’s rather academic, but I did leave with that one takeaway.

[deleted]

Re: Design Thinking Books (2024)

#63

Post by ccppurcell »

bsoles wrote: post #60

Design Thinking is the Data Science of UX: an attempt to gain influence in fields that you don't have expertise in. Even though there might be universal design principle that can be applied in many fields, the Design Thinking people think that they can just come in and design user interfaces, etc. without really having an expertise in the particular field. Design Thinking works for selling consulting and not much els…

Can you give an analogous example for data science? I confess ignorance here, and always took the term at face value. Is the issue that "data science" tries to be agnostic about the source of the data? (I'm not claiming that that is true, just guessing)

Re: Design Thinking Books (2024)

#64

Post by 7tythr33 »

What most people fail to realise is something quite simple about “design” - it’s the discipline of bridging human behaviour and “things” (be that objects or software).

Don Norman’s book covers a lot on human behaviour, which is the correct lens through which to view “design”.

Re: Design Thinking Books (2024)

#66

Post by gond »

turnsout wrote: post #58
gond wrote: post #56

Earlier quoted context omitted.

That is exactly the point. Taking a theory (Systems Thinking), a mental model which has the primary goal of holistically identifying, describing, and understanding wholes and reducing it down to a set of methods/framework out of ease of use (the pragmatism) is exactly the wrong approach in my opinion. Systems Thinking and all of its applications scenarios are based on epistemology. To turn it into a recipe is a wrong…

I practiced Design Thinking at IDEO for 10 years, and I can assure you it's not "one size fits all." And you can onboard an intern or a client CEO in days, without requiring them to internalize a very abstract system for decomposing problems.

>I practiced Design Thinking at IDEO for 10 years

That may possibly explain your motivation but even ten years do not make it right, nor the speed of teaching.

You are saying it yourself: internalising the very abstract system for decomposing and adapting it has a value of its own you cannot replicate by pre-solving it. The spinning-off of Design Thinking only accomplished further segmentation of a space which was already too fractured and was a disservice to the field.

I don’t think we will approach a consensus here, and that’s fine.

Re: Design Thinking Books (2024)

#67

Post by ccppurcell »

al_borland wrote: post #34
yakkomajuri wrote: post #12

I'm a dev and recently picked up "The Design of Everyday Things" as an attempt to become more design-oriented. Everyone raves about this being like the bible of design. So far I'm about 80 pages in and have found it extremely academic and not very practical, sometimes deriving conclusions that are so far from reality that they are a bit concerning, like how a strong password does not matter because once they inevitab…

I was gifted this book my a CIO when in college. She had a dozen copies in her office to hand out to various people. It took me a few tries to get up the will to actually read it. It was years ago, so I don’t remember a lot of details. My main take away was to make controls logical for the thing being controlled. “Norman doors” are the big one, but I often think about it while I’m in my car trying to do something on…

The thing about norman doors is that it's not really a design flaw, not in every case. Like handles on push doors. It's tempting to think of that as a design flaw but more likely it's designed to be mass produced and reversible, the cost of making two (or more) configurations being much higher than the occasional confused user. You could argue this only enhances the metaphor as a lot of design issues occur when things are optimised for the company and not the user.

Re: Design Thinking Books (2024)

#68

Post by jasonhong »

yakkomajuri wrote: post #12

I'm a dev and recently picked up "The Design of Everyday Things" as an attempt to become more design-oriented. Everyone raves about this being like the bible of design. So far I'm about 80 pages in and have found it extremely academic and not very practical, sometimes deriving conclusions that are so far from reality that they are a bit concerning, like how a strong password does not matter because once they inevitab…

I've used The Design of Everyday Things in many classes I teach. I would agree that it's not practical, but that's not its goal. Instead, it gives you frameworks for thinking about things as well as vocabulary for talking about those things.

Off the top of my head, some of the key ideas include:

* Affordances, that objects should have (often visual) cues that give hints as to how to use things * Mental models, that every design has three different models, namely system implementation, design model, and user model, and that the design model and user model should try to match each other * Gulf of Evaluation (the gap between the current system state and people's understanding of it) and Gulf of Execution (the gap between what people want the system to do and how to use the system to do it) * Kinds of Errors and how to design to prevent and recover from them, e.g. slips (chose the right action but accidentally did the wrong thing, e.g. fat finger) vs mistakes (chose the wrong action to do)

What's particularly useful about Norman's book is that these key ideas apply for all kinds of user interfaces, from command-line to GUI to voice-only to AR/VR to AI chatbot. I'd encourage you to think about this book in this kind of framing, that it gives you general frameworks for reasoning and talking about UX problems rather than specific practical solutions.

Re: Design Thinking Books (2024)

#69

Post by codethief »

bsoles wrote: post #60

Design Thinking is the Data Science of UX: an attempt to gain influence in fields that you don't have expertise in. Even though there might be universal design principle that can be applied in many fields, the Design Thinking people think that they can just come in and design user interfaces, etc. without really having an expertise in the particular field. Design Thinking works for selling consulting and not much els…

Uhh… What does Design Thinking have to do with UX? Sure, it could be used to come up with novel ideas for user interfaces but DT (nowadays) is an approach that's several orders of magnitude more general.

Re: Design Thinking Books (2024)

#70

Post by bsoles »

ccppurcell wrote: post #63
bsoles wrote: post #60

Design Thinking is the Data Science of UX: an attempt to gain influence in fields that you don't have expertise in. Even though there might be universal design principle that can be applied in many fields, the Design Thinking people think that they can just come in and design user interfaces, etc. without really having an expertise in the particular field. Design Thinking works for selling consulting and not much els…

Can you give an analogous example for data science? I confess ignorance here, and always took the term at face value. Is the issue that "data science" tries to be agnostic about the source of the data? (I'm not claiming that that is true, just guessing)

Sure. There are many examples of data scientists attempting to use complex Machine Learning and Deep Learning models to predict machine (bearings, gears, etc.) failures from vibration data, where a simple Fourier Transform (FFT) provides a lot more insight and predictive powers about the same problem.

However, spectrum analysis is not something that data scientists learn at school, yet every mechanical/electronics engineer working in the field knows about it. So, without an expertise in a particular field, data scientists often reach for a big hammer, when more specialized tools exist and are known to the experts in the field.

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