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robertogreco : explanation   14

Impakt Festival 2017 - Performance: ANAB JAIN. HQ - YouTube
[Embedded here: http://impakt.nl/festival/reports/impakt-festival-2017/impakt-festival-2017-anab-jain/ ]

"'Everything is Beautiful and Nothing Hurts': @anab_jain's expansive keynote @impaktfestival weaves threads through death, transcience, uncertainty, growthism, technological determinism, precarity, imagination and truths. Thanks to @jonardern for masterful advise on 'modelling reality', and @tobias_revell and @ndkane for the invitation."
https://www.instagram.com/p/BbctTcRFlFI/ ]
anabjain  2017  superflux  death  aging  transience  time  temporary  abundance  scarcity  future  futurism  prototyping  speculativedesign  predictions  life  living  uncertainty  film  filmmaking  design  speculativefiction  experimentation  counternarratives  designfiction  futuremaking  climatechange  food  homegrowing  smarthomes  iot  internetofthings  capitalism  hope  futures  hopefulness  data  dataviz  datavisualization  visualization  williamplayfair  society  economics  wonder  williamstanleyjevons  explanation  statistics  wiiliambernstein  prosperity  growth  latecapitalism  propertyrights  jamescscott  objectivity  technocrats  democracy  probability  scale  measurement  observation  policy  ai  artificialintelligence  deeplearning  algorithms  technology  control  agency  bias  biases  neoliberalism  communism  present  past  worldview  change  ideas  reality  lucagatti  alextaylor  unknown  possibility  stability  annalowenhaupttsing  imagination  ursulaleguin  truth  storytelling  paradigmshifts  optimism  annegalloway  miyamotomusashi  annatsing 
november 2017 by robertogreco
A biologist explains CRISPR to people at five different levels of knowledge
"For the second part of an ongoing series, Wired asked biologist Neville Sanjana to explain CRISPR to five people with different levels of knowledge: a 7-year-old, a high school student, a college student, a grad student, and an expert on CRISPR. As I began to watch, I thought he’d gone off the rails right away with the little kid, but as soon as they connected on a personal issue (allergies), you can see the bridge of understanding being constructed."

[video:https://www.youtube.com/watch?v=sweN8d4_MUg
"CRISPR is a new area of biomedical science that enables gene editing and could be the key to eventually curing diseases like autism or cancer. WIRED has challenged biologist Neville Sanjana to explain this concept to 5 different people; a 7 year-old, a 14 year-old, a college student, a grad student and a CRISPR expert."]

[See also: "A neuroscientist explains a concept at five different levels"
http://kottke.org/17/03/a-neuroscientist-explains-a-concept-at-five-different-levels
https://www.youtube.com/watch?v=opqIa5Jiwuw ]
biology  CRISPR  genetics  nevillesanjana  science  video  explanation  communication  teaching  complexity  classideas  howweteach  2017  genomes 
may 2017 by robertogreco
A neuroscientist explains a concept at five different levels
"Wired recently challenged neuroscientist Bobby Kasthuri to explain what a connectome is to people with five different levels of potential understanding: a 5-year-old, a 13-year-old, a college student, a neuroscience grad student, and an expert neuroscientist. His goal: “every person here can leave with understanding it at some level”.

Watching this, I kept thinking of Richard Feynman, who was particularly adept at describing concepts to non-experts without sacrificing truth or even nuance. See him explain fire, rubber bands, how trains go around curves, and magnets."

[video: https://www.youtube.com/watch?v=opqIa5Jiwuw
"The Connectome is a comprehensive diagram of all the neural connections existing in the brain. WIRED has challenged neuroscientist Bobby Kasthuri to explain this scientific concept to 5 different people; a 5 year-old, a 13 year-old, a college student, a neuroscience grad student and a connectome entrepreneur."

[See also: "A biologist explains CRISPR to people at five different levels of knowledge"
http://kottke.org/17/05/a-biologist-explains-crispr-to-people-at-five-different-levels-of-knowledge
https://www.youtube.com/watch?v=sweN8d4_MUg ]
bobbykasthuri  neuroscience  richardfeynman  science  video  explanation  communication  clarity  complexity  teaching  howweteach  classideas 
may 2017 by robertogreco
Teaching is Compression
"Teaching itself comes in at least two forms. It's not just about broadcasting knowledge. No matter how many students you have, if that's all you're doing you aren't making as much progress as you could. The internet is a powerful tool for Type I teaching, but it can't help much with Type II. That is why it is not a satisfactory replacement.

The second type of teaching is a form of compression, making things easier to understand. I don't mean simply eliding details, or making your proofs more terse. I mean compression in the time it takes to explain an idea and its implications.

Computer science is hard. Logic is hard. And that's fine. But if we leave this world as complicated as we found it then we've failed to do our jobs. Think about it this way: if the next generation learns at the same speed as yours, they won't have time to move beyond you. Type II teaching is what enables Type I progress.

Physics went through a period of compression in the middle of the last century. Richard Feynman's reputation wasn't built on discovering new particles or laws of nature, but for discovering better ways to reason about what we already knew. [1] Mathematics has gone though several rebuilding periods. That's why you can pick up a child's math book today and find negative numbers, the square root of two, and many cheerful facts about the square of the hypotenuse. Every one of those mundane ideas was once the hardest problem in the world. My word, people died in arguments over the Pythagorean Theorem. Now we teach it to kids in a half hour. If that's not progress I don't know what is.

So how do we get there in computer science? How can we simplify what we already know so the next crop learns what they need to put our best efforts to shame?

The second form of progress is closely related to the second form of teaching. To my mind, understanding and explaining are just opposite ends of the same process. The only way to prove that you understand something is to explain it to somebody else. Not even using the knowledge is an airtight proof. That's why teachers are always telling you to show your work, to explain step-by-step how you got to the answer.

The most powerful way I know of to understand and explain is through story. Rendering a complex idea into a simple example, analogy, metaphor or allegory simultaneously achieves compression and a way to spread that idea far and wide. Making a good story also forces you to think hard about ways to drive home both the idea and its implications."
teaching  compression  howweteach  explanation  analogy  2012  carlosbueno  richardfeynman  math  mathematics 
september 2016 by robertogreco
Design Is Mainly About Empathy — Track Changes
"1. The user has a way of thinking about the information they want. Example: “I heard about jousting and it sounds weird so I think I’ll watch some jousting videos.”

2. The information our user needs actually exists a certain way in the world. Example: A database of video information with some metadata are magnetized regions of alloy on a hard drive on a server somewhere in North Carolina.

3. A product designer has represented the information to the user with some degree of abstraction. Example: A web page at a certain URL shows a place to type a search query, a loading indicator, some branding, a sorted list of results with previews, and a plenty of enticing buttons to click on in case your jousting interest flickers out and Christina Aguilera on Jimmy Kimmel could help you pass the time instead.

[screenshot captioned: "Jousting is actually pretty interesting btw"]

Between the magnetized alloy and a user on a couch watching jousting videos is…a bunch of abstraction. So it’s the job of a good product designer to hold all three models of the information in her mind, and build a bridge between them. She covers the gaps between her users and the machine, so her users don’t have to bother. As Alan Cooper puts it:
Computer literacy is a euphemism for forcing human beings to stretch their thinking to understand the inner workings of application logic, rather than having software-enabled products stretch to meet people’s usual ways of thinking.


Let’s take a closer look at those three methods. Alan Cooper tackles all three in the seminal About Face: The Essentials of Interaction Design.

The first one is the user’s mental model. Cooper writes that a lot of people think “electricity flows like water from the wall into the appliances through the little black tube of the electrical cord” when they plug in their vacuum or computer.

Of course, the electricity doesn’t flow like water at all. In the real world, electricity’s implementation model is much more complex. But a simpler view of electricity works just fine for most of us. It’s informative enough to help us understand, for example, that we need to cram a cord into an outlet to charge our computer.

Finally, the represented model is the way the thing ends up looking to the user. This is the part the designer spends their time working on, and the part that people will actually touch.

Here’s the secret for the designer, again from Cooper:
“The closer the represented model comes to the user’s mental model, the easier he will find the application to use and understand.”


Bravo! For a designer, that might mean spending more time talking to users, and less time digging through the API. It might mean that early design phases are better spent researching user psychology instead of tinkering with typography.

The user’s mental model, faulty though it may be, is our guiding light. If we don’t invest effort in understanding that model, it’s going to be really hard to know if our work is successful. Design is mainly about empathy.

Example time. Animation is a great tool for practicing user empathy. Animation is a user interface pattern for aligning a user’s mental model with the product’s represented model. The notifications menu in iOS 9 isn’t physically tucked up underneath the top of the device on a curtain roll, and everyone knows that. But users have mental models of tugging on objects in their world from the near the top to reveal a new temporary state.

[two GIFs (one of blinds, one of the notifications pane in iOS being opened by swiping from the top) captioned "Blinds image courtesy IKEA"]

The thing that’s special about the represented model—Cooper helped me see this—is that it’s the only part a designer can control. We can’t control the implementation model, because a good engineer will use abstractions in the codebase to make it maintainable and safe. And we can’t control our user’s mental model, since it’s shaped by their culture and dozens of other unknowable factors.

As designers, we have the power to manipulate representations. Design is the process of making our users feel awesome by representing the software in a way that meets them where they are."
design  ux  alancooper  richardfeynmann  teaching  empathy  explanation  2016  neilrenicker  representation  ui  mentalmodels  abstraction 
july 2016 by robertogreco
On Repeat - Learning - Source: An OpenNews project
"How to use loops to explain anything"



"GIFs in the Future

I am pretty confident that there are many more ways to use GIFs for journalism. And while I’m not sure what sorts of forms GIFs will take in the future, I urge you to think of ways to bring loops into the world of storytelling on the web in a purposeful, insightful, or just plain humorous way. Because who knows what sorts of impossible or magical or transformative experiences we can create—all with the power of loops."
lenagroeger  gifs  journalism  video  looping  visual  history  animation  animatedgifs  eadweardmuybridge  howthingswork  explanation  probability  communication  classideas  repetition  storytelling  exposuretherapy  giphy 
june 2015 by robertogreco
Don't Explain So Much at Once, and Other Advice from Young Science Readers - Frontiers for Young Minds - Scientific American Blog Network
"Though scientists are often motivated to explain their research to the public, many find themselves floundering with how best to communicate what they do for those with little or no experience in their field of study. Like any skill, translating science for novice readers—especially kids and teens—is developed through practice and feedback. For many scientists these kinds of opportunities can be infrequent enough to make learning from them difficult.

The authors who have written for Frontiers for Young Minds knew going in that they will be helping to create a valuable science resource by translating their work directly for young readers. But many of them have found that having direct access their target audience as reviewers yielded feedback that was not only helpful, but occasionally surprisingly blunt in regards to their communication skills.

Thanks to their frank honesty, the FYM Young Reviewers of our first ~45 manuscripts have revealed many of the pitfalls that scientists face when trying to explain their own work to a novice audience. While we are in the process of compiling this feedback into a how-to guide to help our future authors learn from the experiences of those in the past, I wanted to allow some of the most notable comments from our Young Reviewers to shine in their own right.

Below I have selected eight pieces of feedback that highlight some of the most common pitfalls. I think of this as an important starting place. But as soon as these pitfalls are addressed, I am certain that our Young Reviewers will find more ways for scientists to improve their communication skills.

Explaining your motivation

For any researcher, the justification for their research might seem obvious or intuitive. Assuming your reader automatically understands the motivation behind your research as well is a great way to invite them to disengage or disregard the work as trivial.

“The writers of the article did not make it clear why such an expensive and involved research project was done to begin with ... It seemed like a fruitless task.” —Reviewer, Age 14

Forgetting the basics

Scientists can often forget what a “basic” understanding of their field looks like, and assume something to be a middle-school level of familiarity with a subject when it is actually more representative of an undergraduate major in their second year.

“It would be helpful if they told us how they took the measurement of brains without actually having to remove the brain.” —Reviewer, Age 9

“The point is not clearly expressed. I didn’t understand the main scientific question because there were so many details at the beginning. Maybe state what the main question is earlier in the manuscript.” —Reviewer, Age 10

Interest and reading level of your audience

Years of practice have led researchers to write about their work as dispassionately as possible. Unfortunately this bleeds over into when these researchers write for young audiences. Add the extra limitation of a ~2000-word maximum and the effect becomes even more profound. Authors will fall into the habit of creating dense and nested sentence structures in the interest of saving space. Instead of choosing structures and vocabulary most suited to learning, many will choose the structure that allows them to introduce as many new terms and concepts as possible in the limited space. This leaves the young readers struggling to engage with something that is not only new content, but has all of the excitement of a DVD player instruction manual.

“This seems important, but the way it is written is so boring I can’t even get to the end. Could the authors maybe sound excited about what they are doing?” —Reviewer, Age 12

“(After reading the first two paragraphs) This paper is very long and there are too many words that kids are not going to understand.” —Reviewer, Age 12

“Moving on, some long and confusing Latin words appear. The problem with these Latin words is that they distract from the text, with it becoming less interesting.” —Reviewer, Age 15

Including figures for the authors instead of the readers

Researchers think of figures as ways to visualize data instead of tools for displaying meaning, visualizing difficult concepts, or presenting connections between important pieces of information. Depending on the age group, figures should entice the reader, teach the reader, or foster deeper understanding of key ideas.

“I wish that the pictures were easier to understand just by looking at them. When it takes me a long time just to figure out what they mean, it feels like homework.” —Reviewer, Age 9

“This article is fun. Now, let’s talk about what I don’t really get … I just don’t understand figure 2. I think nobody in the third grade knows what power spectra are.” —Reviewer, Age 8"
science  education  children  kids  learning  teaching  howwelearn  howweteach  explanation  via:anne  2015  audience  motivation  communication 
june 2015 by robertogreco
style.org > The Weight of Rain
[An older Jonathan Corum production: http://13pt.com/projects/nyt110425/ ]

"So when I’m looking at data, or working on an explanatory graphic, these are the moments I’m looking for.

Little “Aha!” moments that I can point to, and say “Look here, something happened,” and then try to explain.

Often those small moments can help lead a reader into the graphic, or help to explain the whole."



"I think many of the infographics we see are really just counting: 190 beers, 190 cups of coffee.

If the only thing you’re doing is coming up with a single number, then you’re doing arithmetic, not visualization.

So I want to make sure that in showing planets I’m not doing some variant of this: 190 planets.

This might be an exaggeration, but it’s the kind of thing I want to avoid.

And I think that the goal of visualization is not finding elaborate ways to encode information. I try to encode as little as possible.

You could imagine taking the same planet data and coming up with any number of geometric shapes to encode it. Maybe the vertical bar is star temperature and the horizontal bars are planet orbits.

But to me this feels like imposing a design on the data, and drawing attention to the design more than the data.

I don’t want my readers to have one finger up here on the key, and another finger down here on the graphic, looking back and forth trying to understand the design. I want the design to disappear.

And I don’t want the reader to have to work hard to decode the information — that’s my job as the designer.

I also want to make sure that I’m not introducing any patterns that don’t exist in the data.

For example, this diagram has the star numbers on the left, and the planet names — the planet letters — on the right. It looks impressive, but the X-like patterns of connecting lines are meaningless. It’s just a reflection of the way the items are ordered, and doesn’t have any interesting meaning in the real world.

There are an infinite number of ways of encoding information.

But just as I wouldn’t ask my readers to learn semaphore or Morse code to read one of my graphics — both of these say “Visualized” — I also don’t want to write microlanguages for my data that readers have to translate. If I do that, I’ve lost my reader before I’ve even started.



And most importantly, I try to keep in mind that visualization is not the same thing as explanation.

If I visualize something and walk away, I’ve only done half the job.



CLOSE
I haven’t shown you many projects this morning, but they do have a theme.

The Curiosity mission is a search for evidence of past water on Mars.

And the Kepler mission is a search for Earth-sized planets in the habitable zone, where liquid water might exist on the surface of a planet.

Both are examples where we — we as humans — are looking for evidence that another form of life might have responded to, or felt, or perhaps even been conscious of ...

... the weight of rain."
jonathancorum  visualization  design  data  2014  mars  change  infographics  space  planets  science  explanation  via:jenlowe 
february 2014 by robertogreco
Education Week: Students Can Learn by Explaining, Studies Say
"“Often students are able to say facts, but not able to understand the underlying mathematics concept, or transfer a problem in math to a similar problem in chemistry,” said Joseph Jay Williams, a cognitive science and online education researcher at the University of California, Berkeley.
For example, a student asked to explain why 2x3=6 cannot simply memorize and parrot the answer, but must understand the underlying relationship between multiplication and addition, Mr. Williams said. Students who can verbally explain why they arrived at a particular answer have proved in prior studies to be more able to catch their own incorrect assumptions and generalize what they learn to other subjects.
“We know generating explanations leads to better educational outcomes generally. When children explain events, they learn more than when just getting feedback about the accuracy of their predictions,” said Cristine H. Legare, an assistant psychology professor and the director of the Cognition, Culture, and Development Laboratory at the University of Texas at Austin."



"Mr. Williams warned, though, that students asked to explain something that seems inconsistent with a previous rule or belief can end up learning less, if they discount the new information.

He found that elementary students who inaccurately interpret one pattern and then are given a single anomaly tend to “explain it away” and believe their mistaken interpretation more strongly. When they are given multiple exceptions to explain, it becomes easier for them to recognize their mistakes."
learning  education  teaching  inquiry-basedlearning  questionasking  explanation  2013  christinelegare  josephjaywilliams  psychology  howwelearn  howweteach  dedregetner  askingquestions 
june 2013 by robertogreco
What does it take to become an expert at anything? - Barking up the wrong tree
"It's quantity and quality. You need tons of time spent training but it has to be the right kind of practice. Just showing up is not enough, you need to continually challenge yourself with the right kind of effort. "Deliberate Practice" is a specifically defined term. It involves goal setting, quick feedback, and countless drills to improve skills with an eye on mastery. It is not "just showing up" and, plain and simple, it's not fun."

* You want practice to be as close to the real challenge as possible. Want to be a boxer? Hitting the bag is not enough. You need to be in a ring, against opponents, like a real match.

* Don't be passive. Testing yourself is far better than reviewing.

* Practice is not just repetition. Be ruthlessly critical and keep trying to improve on the constituent elements of the skill.

* Alone time. Top experts are more likely to be introverts…"

"Have Grit… Find a Great Mentor… Focus on the Negative… Focus on Improvement… Fast Feedback… It's Worth It"
persistence  experts  grit  correction  repetition  imitation  demonstration  explanation  mentors  mindset  mistakes  cv  perfectionism  mastery  skillbuilding  introverts  education  deschooling  unschooling  glvo  prototyping  howwelearn  feedback  learning  practice  via:tealtan  thisandthat  2012  expertise  mentoring  improvement  perseverence  makerstime  makertime  makersschedule 
august 2012 by robertogreco
On Sleep No More, magic and immersive storytelling | Fresh & New(er)
"Towards the close of their talk Pete Higgin had a nice line – “explanation is the killer of wonderment”.

It reminded me of a recent article from Salon on the effect of YouTube on the traditions & social practices of magicians.

“The biggest problem with DVD and YouTube exposure is that it has damaged the skill of learning through asking…

What if we designed exhibitions to have the same ‘dense, cinematic detail’ that Punch Drunk’s productions have? (And trusted visitors to respect and engage with them appropriately through scaffolding the entry experience?)

What if we designed our exhibitions to hold things back from some visitors? And to purposefully make some elements of an exhibition ‘in-accessible’ to all? (The Studio Ghibli Museum in Tokyo is wonderfully designed with some spaces and passages that are only accessible by small children that lead to experiences that only children can have separate from their parents.)

What if we made ‘wonderment’ our Key Performance Indicator?"
theatricality  magic  explanation  parallelism  mitmedialab  colinnightingale  petehiggin  transmedia  storytelling  punchdrunk  via:tealtan  storycode  immersive  exploration  museums  themeparks  theater  exhibitions  inaccessibility  accessibility  nyc  lcproject  experiencedesign  experience  studioghiblimuseum  studioghibli  details  wonder  wonderment  sebchan  2012  sleepnomore  design  medialab 
july 2012 by robertogreco
LESS AND MORE (The 15 Things Charles and Ray Eames Teach Us)
"1. Keep good company
2. Notice the ordinary
3. Preserve the ephemeral
4. Design not for the elite but for the masses
5. Explain it to a child
6. Get lost in the content
7. Get to the heart of the matter
8. Never tolerate “O.K. anything.”
9. Remember your responsibility as a storyteller
10. Zoom out
11. Switch
12. Prototype it
13. Pun
14. Make design your life… and life, your design
15. Leave something behind

Excerpt from The 15 Things Charles and Ray Eames Teach Us by Keith Yamashita"
eames  keithyamashita  design  glvo  explanation  zoom  zooming  prototyping  making  life  howto  wisdom  lists  noticing  company  purpose  howwework  via:preoccupations  zoominginandout 
august 2011 by robertogreco

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