Once Each Day (A Poem for English Teachers)

 

Language is predicated on telling the truth.
It's not that we always tell the truth.
It's that if we rarely or never do,
Language loses its point.
In America today
We expect lies from corporations, governments, and scam charities.
We expect lies from every side
In the name of profit, success, and power.
In a world where everyone customizes what they want to hear
And listens in an echo chamber of self-sameness
To only what they want to believe,
The truth is an orphan any way.
The truth that is important is not spelled with a capital "T".
Truth with a little "t" just means trying
To respect the world and others the best we can
By letting words mingle with things and not just desires.
If you want to know whether your new idea is good or bad,
Ask someone who doesn't love you or hate you,
Who knows some things you don't
And will listen to what you say and not who you are.
The point of truth seeking is not being right.
It is trying to be right
And allowing you may be wrong
And that someone else you don't even like might be right.
The rich fat cats deny Global Warming
So they can keep selling oil.
Hospitals call themselves charities
When they collect every penny from the poor.
Of course in America this is nothing new.
Adrian Mitchell said it so well some time ago
In his poem, "To Whom It May Concern 
(Tell Me Lies about Vietnam)":
"I was run over by the truth one day. 
Ever since the accident I've walked this way 
So stick my legs in plaster 
Tell me lies about Vietnam".
Lessons go unlearned.
We lose more wars
And harm more people
Because we will not teach and learn.
The "English teacher" is the key.
The job is to teach the students to once at least
Tell the little "t" truth each day,
To feel how it sounds on the tongue and looks on the page.
Once each day will keep the devil away.

Language is predicated on telling the truth.

It's not that we always tell the truth.

It's that if we rarely or never do,

Language loses its point.

 

In America today

We expect lies from corporations, governments, and scam charities.

We expect lies from every side

In the name of profit, success, and power.

 

In a world where everyone customizes what they want to hear

And listens in an echo chamber of self-sameness

To only what they want to believe,

The truth is an orphan any way.

 

The truth that is important is not spelled with a capital "T".

Truth with a little "t" just means trying

To respect the world and others the best we can

By letting words mingle with things and not just desires.

 

If you want to know whether your new idea is good or bad,

Ask someone who doesn't love you or hate you,

Who knows some things you don't

And will listen to what you say and not who you are.

 

The point of truth seeking is not being right.

It is trying to be right

And allowing you may be wrong

And that someone else you don't even like might be right.

 

The rich fat cats deny Global Warming

So they can keep selling oil.

Hospitals call themselves charities

When they collect every penny from the poor.

 

Of course in America this is nothing new.

Adrian Mitchell said it so well some time ago

In his poem, "To Whom It May Concern 

(Tell Me Lies about Vietnam)":

 

"I was run over by the truth one day. 

Ever since the accident I've walked this way 

So stick my legs in plaster 

Tell me lies about Vietnam".

 

Lessons go unlearned.

We lose more wars

And harm more people

Because we will not teach and learn.

 

The "English teacher" is the key.

The job is to teach the students to once at least

Tell the little "t" truth each day,

To feel how it sounds on the tongue and looks on the page.

Once each day will keep the devil away.

 

Digital Media and Learning: A Prospective Retrospective

Recently the MacArthur Foundation released an important report on “connected learning” (Ito, Mizuko, Kris Gutiérrez, Sonia Livingstone, Bill Penuel, Jean  Rhodes, Katie Salen, Juliet Schor, Julian Sefton-Green, S. Craig  Watkins. 2013. Connected Learning: An Agenda for Research and Design. Irvine, CA: Digital Media and Learning Research Hub).  This report represents the culmination of years of work on digital media and learning funded by MacArthur.  The MacArthur funded  work has given rise to a distinctive vision and helped launch an international movement devoted to digital media and learning in and out of school.  In earlier days I was a small part of this effort exploring a somewhat different but related stream than connected learning.  I have posted a paper that is a reflection on the report, but only in the indirect sense that the report prompted me to these thoughts, thoughts which are often, I realize, tangential to the MacArthur report. You can find the paper under Publications on this site under the title "Digital Media and Learning: A Prospective Retrospective".

Broadening the Context in Discussions of Education

 

I argue that discussions of learning and assessment should be placed in the context of the dramatic changes in our world.  These changes are fueled by technology and by today’s interacting social, environmental, economic, and civilizational crises.  This context of change involves emerging technologies whose effects are already being felt and technologies on the horizon that can shape a better or worse future depending on how we prepare now for that future.
I want to list just a few of the most salient items that compose the context of change relevant to what students should know and be able to do in a 21st Century world.  I also want to offer a wider reading list for educators. None of these changes are good or bad in and of themselves.  All of them hold out potential for good or ill depending on how we engage with them.
1.  The Producer/Participant Movement.  Thanks to digital technologies, many more people than ever are becoming (and demanding to be) makers, participants, and designers, not just consumers and spectators.  Everyday people are producing, often collaboratively, media of all sorts, science and knowledge, news, ads, and Internet interest-driven learning communities devoted to almost any topic one can imagine. 
Jenkins, Henry (2006).  Convergence Culture: Where Old and New Media Collide.  New York: New York University Press.
Shirky, Clay (2010).  Cognitive Surplus: How Technology Makes Consumers Into Collaborators.  New York: Penguin.
2.  The Fab Movement.  The Fab Movement involves 3D printers and extractors that can make anything from human skin to houses and nearly any other physical object one can think of.  The Fab movement erases the barrier between atoms and bits, since 3D reality-capture technologies can digitize an object that can then be digitally transformed and “printed” out as a new physical object.  In the near future, people will be able readily to print houses for the poor or bombs for terrorism.
Gershenfeld, Neil (2007).  Fab: The Coming Revolution on Your Desktop—From Personal Computers to Personal Fabrication.  New York: Basic Books.
3.  The DIY Biology Movement.  The DIY Biology Movement uses low cost technologies now available to almost anyone to investigate and redesign cells, viruses, DNA, and other biological materials.  DIY biologists are seeking cures for cancer in their homes, but also redesigning viruses that could have good or dire effects.
Wohlson, Marcus (2011).  Biopunk: How DIY Scientists Hack the Software of Life.  New York: Penguin.
4.  The Amateur-Expert Phenomenon.  Today amateurs can use the Internet and readily available technologies to compete with and sometimes out-compete experts in a great many domains.  Credentials mean much less than they used to.
Hitt, Jack (2013).  Bunch of Amateurs: Inside America's Hidden World of Inventors, Tinkerers, and Job Creators.  New York: Broadway.
5. Big Data.  New technologies allow for the collection of massive amounts of data of all sorts and its use in real time, across time, and after action for learning, knowledge building, and successful action for individuals, groups, institutions, and society at large.  Data collecting devices are being incorporated into objects and even people’s bodies allowing people to plan and act in their daily lives based on copious data.
Smolan, Rick & Erwitt, Jennifer (2012).  The Human Face of Big Data.  New York: Against All Odds Production.
6.  The Dangerous Expert Effect.  Big Data and recent research have shown that credentialed experts in a great many domains make very poor predictions (no better than chance) and that their predictions get worse, not better, when they get more data.  Such experts often under-value what they don’t know, over-value what they do know, and look at data through unwarranted generalizations to which they are professionally attached. Networked groups of people and tools, using diverse perspectives, make better predictions.
Silver, Nate (2012).  The Signal and the Noise.  New York: Penguin.
7.  Crowd Sourcing and Collective Intelligence.  Thanks to the failures of narrowly focused experts (like economists in terms of the 2008 recession), there has been, in science and business, a push towards systems of collective intelligence that network diverse points of view from experts and amateurs in different fields with knowledge stored in smart tools and technologies.
Nielsen, Michael (2012).  Reinventing Discovery: The Era of Networked Science. Princeton, NJ: Princeton University Press.
Weinberger, David (2012).  Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room.  New York: Basic Books.
8.  Jobs.  Changes in technology—for example in generalized robots that can be programmed to carry out different functions and in tools for digital fabricating—look like they will soon remove the low labor-cost advantage that led to out-sourcing and the success of countries like China.  They will dramatically change the nature of work, the types of skills needed for success, and the types (and number) of jobs available.  Many new businesses will leverage consumers and digital tools rather than workers for design and production.
Andersen, Chris (2012).  Makers: The New Industrial Revolution.  New York: Crown Business.
9.  Longer Lives.  New research in biology and new technologies—for example, digitally designing new viruses and new forms of life—hold out the possibility of greatly extending human life, some claim even to a form of “immortality”.  In an already crowded world, this is good news for individuals, but, perhaps, bad news for the world.
Church, George, M. & Regis, Ed. (2012).  Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves.  New York: Basic Books.
10. Growing Inequality.  Inequality between the rich and the poor is growing ever greater in the United State and across the world.  In the United States inequality is as bad or worse than it was in the 1890s, the Age of the Robber Barons.  Class has, for the first time, passed race in terms of educational gaps.  Research has clearly shown that high levels of inequality in a society lead to poor levels of health and high levels of social problems for both the rich and poor in the society.
Joseph E. Stiglitz (2012).  The Price of Inequality: How Today’s Divided Society Endangers Our Future.  New York: Norton.
Pickett, K., & Wilkinson, R. (2011). The Spirit Level: Why Greater Equality Makes Societies Stronger. New York: Bloomsbury Press.
11.  New Technologies for Solving our Major Problems.  New technologies are emerging and on the horizon that have the potential to actually solve some of our most serious problems, problems such as global warming, public health, environmental degradation, energy consumption, and housing for the poor.  We hear less about these because of the academic urge to stress disaster and the negative.
Diamandis, Peter H. & Kotler, Steven (2012).  Abundance: The Future is Better Than You Think.  New York: Free Press.
12.  Sustainability, Resilience, and Anti-Fragility.  The effects of global warming and other human-environmental interactions are occurring so much faster than predicted that there may not be time to leverage new technologies and practices.  This has led some people to argue that it is too late for “sustainability” as a goal (which means that people and systems sustain themselves through change). We need to move to either “resilience” (people and systems adapt and transform amidst change) or “anti-fragility” (people or systems are designed actually to get better with change and chaos).
Zolli, Andrew & Healy, Ann Marie (2012).  Resilience: Why Things Bounce Back.  New York: Free Press.
Nassim, Nicholas Taleb (2012).  Antifragile: Things That Gain From Disorder. New York: Random House.
Mainstream discussions of school reform mainly frame issues of learning and assessment in terms of a narrow focus on current technological changes (e.g., adaptive technologies and customization) and not more broadly on the interactions between technology and our fast-changing and high-risk global world.  Such discussions risk being rendered irrelevant by change and, worse, forestalling the contributions education, learning, and assessment can make to saving our world and making a better long-term future for all.
James Paul Gee (2013).  The Anti-Education Era: Creating Smarter Students Through Digital Learning.  New York: Palgrave/Macmillan.

I argue that discussions of learning and assessment should be placed in the context of the dramatic changes in our world.  These changes are fueled by technology and by today’s interacting social, environmental, economic, and civilizational crises.  This context of change involves emerging technologies whose effects are already being felt and technologies on the horizon that can shape a better or worse future depending on how we prepare now for that future.

I want to list just a few of the most salient items that compose the context of change relevant to what students should know and be able to do in a 21st Century world.  I also want to offer a wider reading list for educators. None of these changes are good or bad in and of themselves.  All of them hold out potential for good or ill depending on how we engage with them.

1.  The Producer/Participant Movement.  Thanks to digital technologies, many more people than ever are becoming (and demanding to be) makers, participants, and designers, not just consumers and spectators.  Everyday people are producing, often collaboratively, media of all sorts, science and knowledge, news, ads, and Internet interest-driven learning communities devoted to almost any topic one can imagine. 

Jenkins, Henry (2006).  Convergence Culture: Where Old and New Media Collide.  New York: New York University Press.

Shirky, Clay (2010).  Cognitive Surplus: How Technology Makes Consumers Into Collaborators.  New York: Penguin.

 

2.  The Fab Movement.  The Fab Movement involves 3D printers and extractors that can make anything from human skin to houses and nearly any other physical object one can think of.  The Fab movement erases the barrier between atoms and bits, since 3D reality-capture technologies can digitize an object that can then be digitally transformed and “printed” out as a new physical object.  In the near future, people will be able readily to print houses for the poor or bombs for terrorism.

Gershenfeld, Neil (2007).  Fab: The Coming Revolution on Your Desktop—From Personal Computers to Personal Fabrication.  New York: Basic Books.

 

3.  The DIY Biology Movement.  The DIY Biology Movement uses low cost technologies now available to almost anyone to investigate and redesign cells, viruses, DNA, and other biological materials.  DIY biologists are seeking cures for cancer in their homes, but also redesigning viruses that could have good or dire effects.

Wohlson, Marcus (2011).  Biopunk: How DIY Scientists Hack the Software of Life.  New York: Penguin.

 

4.  The Amateur-Expert Phenomenon.  Today amateurs can use the Internet and readily available technologies to compete with and sometimes out-compete experts in a great many domains.  Credentials mean much less than they used to.

Hitt, Jack (2013).  Bunch of Amateurs: Inside America's Hidden World of Inventors, Tinkerers, and Job Creators.  New York: Broadway.

 

5. Big Data.  New technologies allow for the collection of massive amounts of data of all sorts and its use in real time, across time, and after action for learning, knowledge building, and successful action for individuals, groups, institutions, and society at large.  Data collecting devices are being incorporated into objects and even people’s bodies allowing people to plan and act in their daily lives based on copious data.

Smolan, Rick & Erwitt, Jennifer (2012).  The Human Face of Big Data.  New York: Against All Odds Production.

 

6.  The Dangerous Expert Effect.  Big Data and recent research have shown that credentialed experts in a great many domains make very poor predictions (no better than chance) and that their predictions get worse, not better, when they get more data.  Such experts often under-value what they don’t know, over-value what they do know, and look at data through unwarranted generalizations to which they are professionally attached. Networked groups of people and tools, using diverse perspectives, make better predictions.

Silver, Nate (2012).  The Signal and the Noise.  New York: Penguin.

 

7.  Crowd Sourcing and Collective Intelligence.  Thanks to the failures of narrowly focused experts (like economists in terms of the 2008 recession), there has been, in science and business, a push towards systems of collective intelligence that network diverse points of view from experts and amateurs in different fields with knowledge stored in smart tools and technologies.

Nielsen, Michael (2012).  Reinventing Discovery: The Era of Networked Science. Princeton, NJ: Princeton University Press.

Weinberger, David (2012).  Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room.  New York: Basic Books.

 

8.  Jobs.  Changes in technology—for example in generalized robots that can be programmed to carry out different functions and in tools for digital fabricating—look like they will soon remove the low labor-cost advantage that led to out-sourcing and the success of countries like China.  They will dramatically change the nature of work, the types of skills needed for success, and the types (and number) of jobs available.  Many new businesses will leverage consumers and digital tools rather than workers for design and production.

Andersen, Chris (2012).  Makers: The New Industrial Revolution.  New York: Crown Business.

 

9.  Longer Lives.  New research in biology and new technologies—for example, digitally designing new viruses and new forms of life—hold out the possibility of greatly extending human life, some claim even to a form of “immortality”.  In an already crowded world, this is good news for individuals, but, perhaps, bad news for the world.

Church, George, M. & Regis, Ed. (2012).  Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves.  New York: Basic Books.

 

10. Growing Inequality.  Inequality between the rich and the poor is growing ever greater in the United State and across the world.  In the United States inequality is as bad or worse than it was in the 1890s, the Age of the Robber Barons.  Class has, for the first time, passed race in terms of educational gaps.  Research has clearly shown that high levels of inequality in a society lead to poor levels of health and high levels of social problems for both the rich and poor in the society.

Joseph E. Stiglitz (2012).  The Price of Inequality: How Today’s Divided Society Endangers Our Future.  New York: Norton.

Pickett, K., & Wilkinson, R. (2011). The Spirit Level: Why Greater Equality Makes Societies Stronger. New York: Bloomsbury Press.

 

11.  New Technologies for Solving our Major Problems.  New technologies are emerging and on the horizon that have the potential to actually solve some of our most serious problems, problems such as global warming, public health, environmental degradation, energy consumption, and housing for the poor.  We hear less about these because of the academic urge to stress disaster and the negative.

Diamandis, Peter H. & Kotler, Steven (2012).  Abundance: The Future is Better Than You Think.  New York: Free Press.

 

12.  Sustainability, Resilience, and Anti-Fragility.  The effects of global warming and other human-environmental interactions are occurring so much faster than predicted that there may not be time to leverage new technologies and practices.  This has led some people to argue that it is too late for “sustainability” as a goal (which means that people and systems sustain themselves through change). We need to move to either “resilience” (people and systems adapt and transform amidst change) or “anti-fragility” (people or systems are designed actually to get better with change and chaos).

Zolli, Andrew & Healy, Ann Marie (2012).  Resilience: Why Things Bounce Back.  New York: Free Press.

Nassim, Nicholas Taleb (2012).  Antifragile: Things That Gain From Disorder. New York: Random House.

 

Mainstream discussions of school reform mainly frame issues of learning and assessment in terms of a narrow focus on current technological changes (e.g., adaptive technologies and customization) and not more broadly on the interactions between technology and our fast-changing and high-risk global world.  Such discussions risk being rendered irrelevant by change and, worse, forestalling the contributions education, learning, and assessment can make to saving our world and making a better long-term future for all.

 

For my own views on this context's relevance to education, see:

James Paul Gee (2013).  The Anti-Education Era: Creating Smarter Students Through Digital Learning.  New York: Palgrave/Macmillan.

 

 

Redistribution: A Primer on 21st Century Economic Theory

A teacher wants to get across to her students the evils of redistribution.

She believes redistribution is a socialist, communist, liberal plot to undermine America.
It is the doctrine of moochers and takers not makers and shakers.
It makes people dependent and fails to "incentivize"  them for success.
Redistribution is an out and out evil.
Unfair, unjust, immoral, and unconstitutional.
It undermines the very foundations of society.
It kills the desire  to work hard for low wages.
"How fair would a grading system be that made the A's give points to the B's and C's and D's,
And, God forbid, even to the F's!", she says.
"That's  how redistribution works.
The people who earned it have to give to those who didn't."
Of course, students in a course and people in America do not all start at the same starting line.
Some, with privileged backgrounds, start already many yards ahead.
Others start way behind the line.
The teacher calls it a fair race nonetheless.
Some earned their A through hard work,
But others earned their A by starting well ahead.
Some earned a C because they started way behind
And made more progress than any of the A's.
The teacher is right but in the wrong direction.
For the last many decades wealth in America has been redistributed up not down.
The rich have taken from the middle class and the poor,
And in the act have surpassed the Age of the Robber Barons.
The rich raided everyday people's bank accounts once Glass-Steagall was repealed.
They created a lucrative poverty industry out of payday loans, check cashing, and usurious credit cards.
They harvested companies by laying off workers, lowering wages, and raiding pension funds.
They made derivatives out of liar loans and foreclosed on homes.
They bought politicians, got subsidies, cut health care, and left the rest of us with the bill.
They claimed they had "earned it" when they had inherited wealth or had famous parents.
They demanded meritocracy for others  but no inheritance tax for their  kids so they would not have to compete.
They colluded to rig Libor rates and raise CEO pay, but decried unions.
They had the Supreme Court pass Citizens United so the corporations and the rich could steal elections.
They sought to restrict voting, just in case their money wouldn't turn the trick.
Then they claimed the election was stolen when they lost,
Because it was their God-given right to win.
So the teacher was confused about who the moochers were.
If redistribution is a Commie plot, then our rich are Commies through and through.
Though I suspect the teacher is happy with the rich taking from the rest of us,
After all, they're rich, so they MUST be smart, as any social Darwinist knows.
For our teacher, downward redistribution-- the sort Christ was for-- is evil.
And upward redistribution is good, since when wealth trickles down to the poor the rich can take it again and "grow" the economy.
Our teacher probably calls herself a good Christian,
But she is in fact a devout Milton Friedmanian.
For the record, trickle down--supply side--economics is a fraud and economies grow by consumption.
Workers with no jobs or bad wages can't buy anything.
See, it had nothing really to do with morality but only with capitalism,
A system we should try.
In the 21st Century there is another case for downward redistribution beyond consumption.
It is a sort of Christian argument on steroids for helping those who have fallen behind.
Today our world is imperiled by complex systems and fierce conflicts.
The earth and the human species are challenged as never before.
You don't slay a dragon with an A.
It takes a team whose strength is no better than its weakest link.
Faced with the dragon's fire, you can bet that the best gives to the worst to get them up to speed,
Before the whole team is burnt to a crisp.
If you're a warrior fighting at the dragon's feet,
You don't ask whether the healer was once a slacker or deprived,
You damn well see to it he will be ready to save you when you are about to die,
And vice versa.
That's how to survive a major dungeon in the World of Warcraft.
And that's how the army takes  a hill in a bloody battle in the desert, though in America rich kids don't go to war.
You redistribute your butt off until everyone is the best they can be.
The team becomes better, smarter, and sometimes braver than anyone in it
Then you don't just get a silly A, you gain victory.
The guild gives you the best drop.
And the army gives you a medal for saving not just yourself but all of us.
You earned it, but you couldn't have done it without the team.
The battle for the earth and for life on our planet,
For the survival of the human species,
Is already joined.
The dragon is at the gates.
Don't bring your A to the battle and brag about it,
Or your money and tell us how hard your parents worked to give it to you.
Bring the respect you won when you buffed your team mates so they could help you save the day.
When the dragon roars, you need people to watch your back, not admire your golden ass.
If you don't believe this, as I know you won't,
See what happens when you stand before the dragon alone and show him your A.
Tell him the others are not there  because they didn't get an A.
As you perish, you might even scream, "It's isn't fair, they weren't as good as me".
Ah, but I hear you say, "I've got you now,
I will bring a team of only A's,
People all as good and smart as me.
People who towed the line and did what they were told".
Too bad you didn't know this particular dragon was impervious to a team of only standard skills.
What you really need now is that screwed up dwarf,
The one you earlier denied drops you really didn't need.
What he might have become is what you need now to save yourself.
"But, surely", you say, "Helping should be a matter of charity,
Not the government or the team telling me what to do".
You are right, you should not be forced on the team.
You can sit it out and hope those you wouldn't help will help you.
But perhaps I'm wrong,
And you'll be just fine,
Alone with your own kind. 

She believes redistribution is a socialist, communist, liberal plot to undermine America.

It is the doctrine of moochers and takers not makers and shakers.

It makes people dependent and fails to "incentivize"  them for success.

 

Redistribution is an out and out evil.

Unfair, unjust, immoral, and unconstitutional.

It undermines the very foundations of society.

It kills the desire  to work hard for low wages.

 

"How fair would a grading system be that made the A's give points to the B's and C's and D's,

And, God forbid, even to the F's!", she says.

"That's  how redistribution works.

The people who earned it have to give to those who didn't."

 

Of course, students in a course and people in America do not all start at the same starting line.

Some, with privileged backgrounds, start already many yards ahead.

Others start way behind the line.

The teacher calls it a fair race nonetheless.

 

Some earned their A through hard work,

But others earned their A by starting well ahead.

Some earned a C because they started way behind

And made more progress than any of the A's.

 

The teacher is right but in the wrong direction.

For the last many decades wealth in America has been redistributed up not down.

The rich have taken from the middle class and the poor,

And in the act have surpassed the Age of the Robber Barons.

 

The rich raided everyday people's bank accounts once Glass-Steagall was repealed.

They created a lucrative poverty industry out of payday loans, check cashing, and usurious credit cards.

They harvested companies by laying off workers, lowering wages, and raiding pension funds.

They made derivatives out of liar loans and foreclosed on homes.

 

They bought politicians, got subsidies, cut health care, and left the rest of us with the bill.

They claimed they had "earned it" when they had inherited wealth or had famous parents.

They demanded meritocracy for others  but no inheritance tax for their  kids so they would not have to compete.

They colluded to rig Libor rates and raise CEO pay, but decried unions.

 

They had the Supreme Court pass Citizens United so the corporations and the rich could steal elections.

They sought to restrict voting, just in case their money wouldn't turn the trick.

Then they claimed the election was stolen when they lost,

Because it was their God-given right to win.

 

So the teacher was confused about who the moochers were.

If redistribution is a Commie plot, then our rich are Commies through and through.

Though I suspect the teacher is happy with the rich taking from the rest of us,

After all, they're rich, so they MUST be smart, as any social Darwinist knows.

 

For our teacher, downward redistribution-- the sort Christ was for-- is evil.

And upward redistribution is good, since when wealth trickles down to the poor the rich can take it again and "grow" the economy.

Our teacher probably calls herself a good Christian,

But she is in fact a devout Milton Friedmanian.

 

For the record, trickle down--supply side--economics is a fraud and economies grow by consumption.

Workers with no jobs or bad wages can't buy anything.

See, it had nothing really to do with morality but only with capitalism,

A system we should try.

 

In the 21st Century there is another case for downward redistribution beyond consumption.

It is a sort of Christian argument on steroids for helping those who have fallen behind.

Today our world is imperiled by complex systems and fierce conflicts.

The earth and the human species are challenged as never before.

 

You don't slay a dragon with an A.

It takes a team whose strength is no better than its weakest link.

Faced with the dragon's fire, you can bet that the best gives to the worst to get them up to speed,

Before the whole team is burnt to a crisp.

 

If you're a warrior fighting at the dragon's feet,

You don't ask whether the healer was once a slacker or deprived,

You damn well see to it he will be ready to save you when you are about to die,

And vice versa.

 

That's how to survive a major dungeon in the World of Warcraft.

And that's how the army takes  a hill in a bloody battle in the desert, though in America rich kids don't go to war.

You redistribute your butt off until everyone is the best they can be.

The team becomes better, smarter, and sometimes braver than anyone in it

 

Then you don't just get a silly A, you gain victory.

The guild gives you the best drop.

And the army gives you a medal for saving not just yourself but all of us.

You earned it, but you couldn't have done it without the team.

 

The battle for the earth and for life on our planet,

For the survival of the human species,

Is already joined.

The dragon is at the gates.

 

Don't bring your A to the battle and brag about it,

Or your money and tell us how hard your parents worked to give it to you.

Bring the respect you won when you buffed your team mates so they could help you save the day.

When the dragon roars, you need people to watch your back, not admire your golden ass.

 

If you don't believe this, as I know you won't,

See what happens when you stand before the dragon alone and show him your A.

Tell him the others are not there  because they didn't get an A.

As you perish, you might even scream, "It's isn't fair, they weren't as good as me".

 

Ah, but I hear you say, "I've got you now,

I will bring a team of only A's,

People all as good and smart as me.

People who towed the line and did what they were told".

 

Too bad you didn't know this particular dragon was impervious to a team of only standard skills.

What you really need now is that screwed up dwarf,

The one you earlier denied drops you really didn't need.

What he might have become is what you need now to save yourself.

 

"But, surely", you say, "Helping should be a matter of charity,

Not the government or the team telling me what to do".

You are right, you should not be forced on the team.

You can sit it out and hope those you wouldn't help will help you.

 

But perhaps I'm wrong,

And you'll be just fine,

Alone with your own kind. 

 

 

Can Technology-Rich Learning Close the Participation Gap?

 

Can Technology-Rich Learning Close the Digital Participation Gap?*
The short answer to the question this article addresses is: “No, technology-rich learning cannot close the digital participation gap”.  Something else can, but that something else would require a political will missing in the United State today.
What is the digital participation gap?  It is a gap between the rich and the poor.  It is not a gap that can be solved by equipment.  While it is true that poor kids have access to less and less good technology, solving this problem will not get rid of the gap.  We can see this if we look at books and the reading gap before we look at technology (really, other technologies, since literacy is a technology).
We have long had a reading gap.  Poor kids learn to read less well than rich ones.  Just giving poor kids books does not begin to close the gap.  How much good giving books does—even if it does any good at all—depends on what you DO with the books.  The same is true of computers, video games, and other forms of media and multimedia.  It is not what you have, but what you do with what you have and who you do it with.
What makes books good for preparing for and doing well in school?  Many things, of course, but two are most important.  First is interactive talk of a certain sort.  Second is experience of a certain sort.  Talk and experience are crucial to book-rich learning. They are, as we will see, crucial to technology-rich learning, as well.
The sort of interactive talk around books that is good for and in school is sustained dialogic talk that: a) stresses connections among books and the world; b) stresses thinking about thinking and language about language (“going meta”); and c) that helps young people read like writers (Why is this written this way?  How would I say it, write it?  This is a form of “going meta”). 
It is essential, too, that this talk be done in a context of respect, support, and nurturing that we associate with “attachment parenting” for younger kids.  Such “attachment mentoring” can lead to so-called “non-cognitive skills”, skills like confidence, persistence, conscientiousness, dealing with failure, accepting challenges, and delayed gratification.  These non-cognitive skills correlate with success in school, finishing college, and success in work better than does IQ.
The sorts of experiences that are good for and in school are ones that give a learner what I call “situated (or embodied) meanings” for words in oral and written language.  And, by the way, oral and written language should never be detached from each other.  Special forms of writing and reading, like the language of physics or of video gaming, are associated with special forms of talking and vice-versa.
Any language like English is composed of a great many different styles of language (or what linguists call “registers” or what I have called elsewhere, “social languages”).  These styles are things like the “language of law”, “the language of physics”, the “language of video gamers”, “the language of street gangs”, and so on through a long and ever growing list.  School and life are about learning new styles of language tied to new identities and new activities as we learn new ways of being in the world.
If a person can associate images, actions, experiences, goals, or interactive dialogue with words, that person has situated meanings for those words.  If a person can only associate other words (definitions, paraphrases) with words, then that person has only verbal meanings for those words, not situated meanings.  
If you try to read a video game manual before you have ever played a game, you can, at best, associate definitions and paraphrases with the words in the text.  The manual is boring and close to useless, when it is not simply inexplicable.  If, however, you play the game for hours—you do not have to play at all well—then when you pick up the manual again everything will be clear. 
Now you will be able to associate images, actions, experiences, goals, and dialogue from the game with each of the words in the text.  You will have lived in the world the manual is about and will know how the words of the text apply to that world to describe it and allow you to solve problems in it.  
The same thing is true for any text, for example, for a middle school science text.  If you have lived in (mucked around in) the world it is about and applies to, you have situated understandings for the words in the text and can use the text to facilitate problem solving.  If you have not had such experiences, then all you have, at best, are verbal meanings.   These may be fine for passing skill-and-drill paper-and-pencil tests, but they are not fine for deep understanding or problem solving.
Because situated meanings are important for real understanding and problem solving, today most games build the manual right into the game. The game gives language “just in time”, when you can immediately put it to use and see how it applies in the virtual world.  Or it gives language “on demand”, when the player needs it, wants it, and can cope with large blocks of it out of the context of the game (as, for example, with the virtual encyclopedia that comes with the game Civilization).  Language should work the same way in school: just in time and on demand.
We humans communicate in oral and written language (and extensions thereof, like the language of mathematics).  Any understandings we have gained from the world, technology, art, or science have to be communicated in language (or some other representational system) to be shared and become a “common wealth”.  
Knowledge is not pure thought.  It is thought and the work of inquiry translated into appropriately communicative styles of language (like the special languages of literary criticism, video games, law, anime, or physics).  So technology-rich learning is always and also language-rich learning.  We cannot close the digital gap without closing the literacy gap and we must close them together.
Learning to use any technology—whether this be video games, digital video, digital fabrication, social media, blogs, web quests, or anything else—is a “literacy” in the sense that, just as with books, we need to learn to “read” (consume meanings) and “write” (produce meanings).  There are ways to “read” (play) video games that lead to success and ways that do not.  There are ways to “write” them well or poorly.
In fact, for video games, “reading” (playing) is already a type of producing (thinking like a designer).  Good gamers must think critically about how a game is designed in order to leverage that design for their own goals.  But that is true of books too:  good readers read like writers (designers).  
There are ways to “write” video games, to design them.  In fact, today many video games come with a version of the software by which they were made and players can “mod” (modify) them, redesigning small or large parts of the game.  Such “writing” (modding) is the higher value-added end of gaming.  It can lead to 21st Century skills with technology.  
But, then, writing has always been the higher value-added end of print literacy.  Unfortunately, both writing and modding tend to be the preserves of the more privileged kids, though popular culture today does offer more kids the opportunity to write (e.g., fan fiction) or mod (e.g., interest-driven web sites devoted to fans of a give game) than ever before.  However, less privileged kids often need mentoring to enter these sites and often, too, need higher literacy skills.
When I say experiences in the world are the foundation for situated meanings for language, I am pointing to the importance of images, actions, goals, and dialogue.  I am, in a sense, repeating what Paulo Freire said long ago when he argued for the priority and importance of “reading the world” to “reading the word”.  However, not all experiences in the world are equally good for creating situated meanings.
Humans think and learn best when the experiences they have in the world have certain key properties.  Some of these properties are: 
a) learners have clear goals for taking an action in the experience, an action that they care about; 
b) learners gain good feedback as they seek to accomplish the goal, including feedback that might make them rethink their goals; 
c) learners are actively encouraged to compare and contrast this experience to other related experiences in order to find patterns (generalizations) in experience; 
d) learners are encouraged to think about and talk about their assumptions, hypotheses, and strategies while acting and after action; e) learners hear others talk about their assumptions, hypotheses and strategies as they attempted to accomplish the same or a similar action (often in an “after action review session”); 
f) learners are encouraged to persist past failure, explore, take risks, and innovate (and, thus, the cost of failure cannot be too high); 
g) learners hear language—sometimes specialist or academic form of language—that   fits the experience and the actions and goals that are an integral part of it; and h) learners are assessed on multiple variables sensitive to growth across time (which can be “U-shaped”, that is go up, then down, the up again) and useful for planning new actions and experiences.
Experience missing these features—which is too often the case when learners are left free in an “anything goes” environment as a way to empower them (it doesn’t)—is not as effective for learning, especially for newcomers.  Texts minus well-designed experiences are equally bad and create a significant equity gap when poor children have the text but little experience and richer children have both.
Technology rich learning also needs to have these features—and indeed technology can be used to create and enhance these features—or the technology can be dispensed with.  It will have no good lasting effects and it may well create more gaps than it closes.
So back to our question: Can technology-rich learning close the digital gap?  The answer is no, no more than books can close the literacy gap.  These gaps are caused by access to sustained interactive talk with a adults and peers; practice diverse styles of oral and written language, including academic styles; attachment mentoring; and well-designed, well-mentored experiences in the world.  
These factors are most effective when they start early in the home well before school has begun.  Their absence is extremely hard to make up for when they have been missing early, though not impossible.  As a country, if we want to close gaps, we need to ensure that all children get these factors early in life.  They are the foundations of learning, language development, school success, and success in work and in society as an effective civic participant.  
Early and late, we need to use books and technology—anything we can get our hands on, well integrated—to give learners situated meanings.  These are the meanings that give people power over texts and the world.  
Our current paradigm of schooling, which stresses age-grading, assessing by standardized amounts of time, and texts torn out of the worlds they are about, are not up to this task.  That is why we still have the gaps in the first place.
Today, out of school in popular culture young people (really everyone) can enter a new and different educational system.  They can enter what I call the “passionate affinity school system”.  This system is technology-rich, language-rich, literacy-rich, and socially-rich when it operates at its best.  At its best it is a gold standard to which schools can aspire and which can help us think about real paradigm change for school.
For any interest you can think of—making digital video, designing all sorts of things, women’s health, pet care, video gaming, fan fiction, citizen science, robotics, anime, and many more—people today can enter interest-driven web sites to discuss, interact over, and produce things in the service of this interest.  Better yet some people on these sites gain a real passion for this interest, put in thousands of hours of practice, and become real masters—often better than credentialed experts—of the domain.  On such sites people are helped and mentored to fan their interest into a real passion that fuels lots of practice and growth towards mastery.
These sorts of interest-driven sites I call “passionate affinity spaces”.  I call them this because everyone in them is there, not because of their age, race, background, or skills, but because of an interest that might be fueled into a passion.  They have an affinity for others with this interest and respect for the passion even if they choose to stay at the level on interest alone.  The come to share common goals, values, skills, and endeavors.  Their differences in life experiences are leveraged for the good of the space as it pools difference to create an expansive collective intelligence that draws on far more experiences and skills than any one person or one type of person could have.
To take one example of a passionate affinity space: people young and old using 3D software of various sorts on various web sites to design (and sometimes sell) virtual clothes, houses, furniture, and landscapes for the video game The Sims, a life and community simulator and the bestselling video game in history.  Thanks now to digital fabrication tools, by the way, any of these virtual things could be or soon will be able to be “printed” into real objects.  Further, thanks to reality capture tools, any physical object can be made into a digital one, transformed, and made back into a physical object.  Bits and atoms are now interchangeable.
In passionate affinity spaces age does not matter.  Time does not matter.  What matters is interest, passion, practice, mastery, talk, shared experiences, feedback, mentoring, production and not just consumption.  Leadership is porous, on some days a person leads or mentors and on other days he or she follows or gets mentored.  People construct tutorials and learning for each other and they discuss, negotiate and set high standards.  They pick up 21st century skills—skills like the ability to design and innovate, to collaborate, and to deal with complexity, technical information, and new technologies—in the context of clear actions and clear goals fueled by interest or passion.  On a design site for the Sims, people use a plethora of specialist language concerned with the Sims, design, and software, but their understandings are always situated in experiences, interactions, and mentoring.  
Books and digital technologies can be tools for better social interactions, richer experiences, and new styles of oral and written language.  When they are such tools, then learning is rich and it is not only the rich who lean.  When they are not such tools, they can create gaps, but they cannot close them.
*For research relevant to the claims in this article, see: Gee, J. P., Situated Learning and Language (Routledge, 2004); Gee, J.P. & Hayes, E.R., Women as Gamers: The Sims and 21st Century Learning (Palgrave/Macmillan, 2010); Gee, J,P. & Hayes, E.R., Language and Learning in the Digital Age (Routledge, 2011); and Tough, P., How Children Succeed (Houghton Mifflin, 2012).

The short answer to the question this piece  addresses is: “No, technology-rich learning cannot close the digital participation gap”.  Something else can, but that something else would require a political will missing in the United State today.

What is the digital participation gap?  It is a gap between the rich and the poor.  It is not a gap that can be solved by equipment.  While it is true that poor kids have access to less and less good technology, solving this problem will not get rid of the gap.  We can see this if we look at books and the reading gap before we look at technology (really, other technologies, since literacy is a technology).

We have long had a reading gap.  Poor kids learn to read less well than rich ones.  Just giving poor kids books does not begin to close the gap.  How much good giving books does—even if it does any good at all—depends on what you DO with the books.  The same is true of computers, video games, and other forms of media and multimedia.  It is not what you have, but what you do with what you have and who you do it with.

What makes books good for preparing for and doing well in school?  Many things, of course, but two are most important.  First is interactive talk of a certain sort.  Second is experience of a certain sort.  Talk and experience are crucial to book-rich learning. They are, as we will see, crucial to technology-rich learning, as well.

The sort of interactive talk around books that is good for and in school is sustained dialogic talk that: a) stresses connections among books and the world; b) stresses thinking about thinking and language about language (“going meta”); and c) that helps young people read like writers (Why is this written this way?  How would I say it, write it?  This is a form of “going meta”). 

It is essential, too, that this talk be done in a context of respect, support, and nurturing that we associate with “attachment parenting” for younger kids.  Such “attachment mentoring” can lead to so-called “non-cognitive skills”, skills like confidence, persistence, conscientiousness, dealing with failure, accepting challenges, and delayed gratification.  These non-cognitive skills correlate with success in school, finishing college, and success in work better than does IQ.

The sorts of experiences that are good for and in school are ones that give a learner what I call “situated (or embodied) meanings” for words in oral and written language.  And, by the way, oral and written language should never be detached from each other.  Special forms of writing and reading, like the language of physics or of video gaming, are associated with special forms of talking and vice-versa.

Any language like English is composed of a great many different styles of language (or what linguists call “registers” or what I have called elsewhere, “social languages”).  These styles are things like the “language of law”, “the language of physics”, the “language of video gamers”, “the language of street gangs”, and so on through a long and ever growing list.  School and life are about learning new styles of language tied to new identities and new activities as we learn new ways of being in the world.

If a person can associate images, actions, experiences, goals, or interactive dialogue with words, that person has situated meanings for those words.  If a person can only associate other words (definitions, paraphrases) with words, then that person has only verbal meanings for those words, not situated meanings.  

If you try to read a video game manual before you have ever played a game, you can, at best, associate definitions and paraphrases with the words in the text.  The manual is boring and close to useless, when it is not simply inexplicable.  If, however, you play the game for hours—you do not have to play at all well—then when you pick up the manual again everything will be clear. 

Now you will be able to associate images, actions, experiences, goals, and dialogue from the game with each of the words in the text.  You will have lived in the world the manual is about and will know how the words of the text apply to that world to describe it and allow you to solve problems in it.  

The same thing is true for any text, for example, for a middle school science text.  If you have lived in (mucked around in) the world it is about and applies to, you have situated understandings for the words in the text and can use the text to facilitate problem solving.  If you have not had such experiences, then all you have, at best, are verbal meanings.   These may be fine for passing skill-and-drill paper-and-pencil tests, but they are not fine for deep understanding or problem solving.

Because situated meanings are important for real understanding and problem solving, today most games build the manual right into the game. The game gives language “just in time”, when you can immediately put it to use and see how it applies in the virtual world.  Or it gives language “on demand”, when the player needs it, wants it, and can cope with large blocks of it out of the context of the game (as, for example, with the virtual encyclopedia that comes with the game Civilization).  Language should work the same way in school: just in time and on demand.

We humans communicate in oral and written language (and extensions thereof, like the language of mathematics).  Any understandings we have gained from the world, technology, art, or science have to be communicated in language (or some other representational system) to be shared and become a “common wealth”.  

Knowledge is not pure thought.  It is thought and the work of inquiry translated into appropriately communicative styles of language (like the special languages of literary criticism, video games, law, anime, or physics).  So technology-rich learning is always and also language-rich learning.  We cannot close the digital gap without closing the literacy gap and we must close them together.

Learning to use any technology—whether this be video games, digital video, digital fabrication, social media, blogs, web quests, or anything else—is a “literacy” in the sense that, just as with books, we need to learn to “read” (consume meanings) and “write” (produce meanings).  There are ways to “read” (play) video games that lead to success and ways that do not.  There are ways to “write” them well or poorly.

In fact, for video games, “reading” (playing) is already a type of producing (thinking like a designer).  Good gamers must think critically about how a game is designed in order to leverage that design for their own goals.  But that is true of books too:  good readers read like writers (designers).  

There are ways to “write” video games, to design them.  In fact, today many video games come with a version of the software by which they were made and players can “mod” (modify) them, redesigning small or large parts of the game.  Such “writing” (modding) is the higher value-added end of gaming.  It can lead to 21st Century skills with technology.  

But, then, writing has always been the higher value-added end of print literacy.  Unfortunately, both writing and modding tend to be the preserves of the more privileged kids, though popular culture today does offer more kids the opportunity to write (e.g., fan fiction) or mod (e.g., interest-driven web sites devoted to fans of a give game) than ever before.  However, less privileged kids often need mentoring to enter these sites and often, too, need higher literacy skills.

When I say experiences in the world are the foundation for situated meanings for language, I am pointing to the importance of images, actions, goals, and dialogue.  I am, in a sense, repeating what Paulo Freire said long ago when he argued for the priority and importance of “reading the world” to “reading the word”.  However, not all experiences in the world are equally good for creating situated meanings.

Humans think and learn best when the experiences they have in the world have certain key properties.  Some of these properties are: 

a) learners have clear goals for taking an action in the experience, an action that they care about; 

b) learners gain good feedback as they seek to accomplish the goal, including feedback that might make them rethink their goals; 

c) learners are actively encouraged to compare and contrast this experience to other related experiences in order to find patterns (generalizations) in experience; 

d) learners are encouraged to think about and talk about their assumptions,hypotheses, and strategies while acting and after action; e) learners hear others talk about their assumptions, hypotheses and strategies as they attempted to accomplish the same or a similar action (often in an “after action review session”); 

f)  learners are encouraged to persist past failure, explore, take risks, and innovate (and, thus, the cost of failure cannot be too high); 

g) learners hear language—sometimes specialist or academic form of language—that   fits the experience and the actions and goals that are an integral part of it; and

h) learners are assessed on multiple variables sensitive to growth across time (which can be “U-shaped”, that is go up, then down, the up again) and useful for planning new actions and experiences.

 

Experience missing these features—which is too often the case when learners are left free in an “anything goes” environment as a way to empower them (it doesn’t)—is not as effective for learning, especially for newcomers.  Texts minus well-designed experiences are equally bad and create a significant equity gap when poor children have the text but little experience and richer children have both.

Technology rich learning also needs to have these features—and indeed technology can be used to create and enhance these features—or the technology can be dispensed with.  It will have no good lasting effects and it may well create more gaps than it closes.

So back to our question: Can technology-rich learning close the digital gap?  The answer is no, no more than books can close the literacy gap.  These gaps are caused by access to sustained interactive talk with a adults and peers; practice diverse styles of oral and written language, including academic styles; attachment mentoring; and well-designed, well-mentored experiences in the world.  

These factors are most effective when they start early in the home well before school has begun.  Their absence is extremely hard to make up for when they have been missing early, though not impossible.  As a country, if we want to close gaps, we need to ensure that all children get these factors early in life.  They are the foundations of learning, language development, school success, and success in work and in society as an effective civic participant.  

Early and late, we need to use books and technology—anything we can get our hands on, well integrated—to give learners situated meanings.  These are the meanings that give people power over texts and the world.  

Our current paradigm of schooling, which stresses age-grading, assessing by standardized amounts of time, and texts torn out of the worlds they are about, are not up to this task.  That is why we still have the gaps in the first place.

Today, out of school in popular culture young people (really everyone) can enter a new and different educational system.  They can enter what I call the “passionate affinity school system”.  This system is technology-rich, language-rich, literacy-rich, and socially-rich when it operates at its best.  At its best it is a gold standard to which schools can aspire and which can help us think about real paradigm change for school.

For any interest you can think of—making digital video, designing all sorts of things, women’s health, pet care, video gaming, fan fiction, citizen science, robotics, anime, and many more—people today can enter interest-driven web sites to discuss, interact over, and produce things in the service of this interest.  Better yet some people on these sites gain a real passion for this interest, put in thousands of hours of practice, and become real masters—often better than credentialed experts—of the domain.  On such sites people are helped and mentored to fan their interest into a real passion that fuels lots of practice and growth towards mastery.

These sorts of interest-driven sites I call “passionate affinity spaces”.  I call them this because everyone in them is there, not because of their age, race, background, or skills, but because of an interest that might be fueled into a passion.  They have an affinity for others with this interest and respect for the passion even if they choose to stay at the level on interest alone.  The come to share common goals, values, skills, and endeavors.  Their differences in life experiences are leveraged for the good of the space as it pools difference to create an expansive collective intelligence that draws on far more experiences and skills than any one person or one type of person could have.

To take one example of a passionate affinity space: people young and old using 3D software of various sorts on various web sites to design (and sometimes sell) virtual clothes, houses, furniture, and landscapes for the video game The Sims, a life and community simulator and the bestselling video game in history.  Thanks now to digital fabrication tools, by the way, any of these virtual things could be or soon will be able to be “printed” into real objects.  Further, thanks to reality capture tools, any physical object can be made into a digital one, transformed, and made back into a physical object.  Bits and atoms are now interchangeable.

In passionate affinity spaces age does not matter.  Time does not matter.  What matters is interest, passion, practice, mastery, talk, shared experiences, feedback, mentoring, production and not just consumption.  Leadership is porous, on some days a person leads or mentors and on other days he or she follows or gets mentored.  People construct tutorials and learning for each other and they discuss, negotiate and set high standards.  They pick up 21st century skills—skills like the ability to design and innovate, to collaborate, and to deal with complexity, technical information, and new technologies—in the context of clear actions and clear goals fueled by interest or passion.  On a design site for the Sims, people use a plethora of specialist language concerned with the Sims, design, and software, but their understandings are always situated in experiences, interactions, and mentoring.  

Books and digital technologies can be tools for better social interactions, richer experiences, and new styles of oral and written language.  When they are such tools, then learning is rich and it is not only the rich who lean.  When they are not such tools, they can create gaps, but they cannot close them.

 

*For research relevant to the claims in this article, see: Gee, J. P., Situated Learning and Language (Routledge, 2004); Gee, J.P. & Hayes, E.R., Women as Gamers: The Sims and 21st Century Learning (Palgrave/Macmillan, 2010); Gee, J,P. & Hayes, E.R., Language and Learning in the Digital Age (Routledge, 2011); and Tough, P., How Children Succeed (Houghton Mifflin, 2012).

 

 

 

 

 

Big "G" Games

A digital game is a play-based, well-designed, problem-solving experience meant to create motivation, engagement, and often creativity.  Humans learn best from well-mentored, guided experience centered on interesting problems to solve, clear goals, copious feedback, and a relatively low cost for failure.  This is what good games supply.

Digital games can be virtual worlds, augmented reality, alternative reality, or collective intelligence in format.  But the game itself—as a piece of digital media (or even transmedia)—is only part of the equation.  People interact socially around games.  They play them collaboratively or competitively, discuss them, read about them, consult strategy guides, share strategies, and “mod” (modify) them in various ways.  These social interactions around a game—all the sorts of social interactions inside or outside a game that the game inspires, encourages, or enhances—is often call “the meta-game”.  
Good game designers design games to enable good social interactions and they reflect on the possible positive synergies between the game and the meta-game.  For example, Nintendo enabled kids to share Pokemon in their Pokemon games via a connection between their games devices to encourage social interactions around the games, interactions which can take on a life of their own.
Today, interest-driven, passion-fuelled, “affinity spaces” on the Internet are one crucially important part of the meta-game around games.  These are sites where people with a shared passion for a game and its problems organize themselves to take the game further.   Such affinity spaces are learning spaces where people of different ages and abilities mentor each other, develop and share expertise in various areas, and invite anyone with an interest in the game to learn more and possibly flame an interest into a passion.  Affinity spaces engage with discussion, co-mentoring, tutoring, critique, reflection, “theory crafting” (explicating the technical underpinnings of the game as a rule system), modding, designing, writing, and relating the game and its problem-solving space to other interests and real world issues.   Affinity spaces are well-designed, social learning spaces that can lead people to different forms of mastery which they can then share with others.  They are a form of collective intelligence fueled by a game.  They enable people to form a bond with others based on their shared affinity for a game, a bond that can transcend divisions based on age, race, class, gender, ability, or life experiences, while still recruiting the knowledge stored in each of these differences.
Good game designers design not games per se, but a system made up of a game, a meta-game (various and sundry social interactions around the game), and affinity spaces that organize the meta-game explicitly for learning and mastery.
Designers of games for impact (e.g., for learning, health, civic participation, training, etc.) think deeply about how to distribute different aspects of learning across the game, the meta-game, and associated affinity spaces.  They design a whole integrated, interacting system made up of the three elements. This three-element, integrated, interacting system is what we call the big “G” Game, to distinguish it from the game as a piece of digital media.  Designers of games for impact are, in reality and at their best, designers of big “G” Games for impact.

A digital game is a play-based, well-designed, problem-solving experience meant to create motivation, engagement, and often creativity.  Humans learn best from well-mentored, guided experience centered on interesting problems to solve, clear goals, copious feedback, and a relatively low cost for failure.  This is what good games supply.

Digital games can be virtual worlds, augmented reality, alternative reality, or collective intelligence in format.  But the game itself—as a piece of digital media (or even transmedia)—is only part of the equation.  People interact socially around games.  They play them collaboratively or competitively, discuss them, read about them, consult strategy guides, share strategies, and “mod” (modify) them in various ways.  These social interactions around a game—all the sorts of social interactions inside or outside a game that the game inspires, encourages, or enhances—is often call “the meta-game”.  

Good game designers design games to enable good social interactions and they reflect on the possible positive synergies between the game and the meta-game.  For example, Nintendo enabled kids to share Pokemon in their Pokemon games via a connection between their games devices to encourage social interactions around the games, interactions which can take on a life of their own.

Today, interest-driven, passion-fuelled, “affinity spaces” on the Internet are one crucially important part of the meta-game around games.  These are sites where people with a shared passion for a game and its problems organize themselves to take the game further.   Such affinity spaces are learning spaces where people of different ages and abilities mentor each other, develop and share expertise in various areas, and invite anyone with an interest in the game to learn more and possibly flame an interest into a passion.  Affinity spaces engage with discussion, co-mentoring, tutoring, critique, reflection, “theory crafting” (explicating the technical underpinnings of the game as a rule system), modding, designing, writing, and relating the game and its problem-solving space to other interests and real world issues.   Affinity spaces are well-designed, social learning spaces that can lead people to different forms of mastery which they can then share with others.  They are a form of collective intelligence fueled by a game.  They enable people to form a bond with others based on their shared affinity for a game, a bond that can transcend divisions based on age, race, class, gender, ability, or life experiences, while still recruiting the knowledge stored in each of these differences.

Good game designers design not games per se, but a system made up of a game, a meta-game (various and sundry social interactions around the game), and affinity spaces that organize the meta-game explicitly for learning and mastery.

Designers of games for impact (e.g., for learning, health, civic participation, training, etc.) think deeply about how to distribute different aspects of learning across the game, the meta-game, and associated affinity spaces.  They design a whole integrated, interacting system made up of the three elements. This three-element, integrated, interacting system is what I (and others, such as David Shaffer) call the big “G” Game, to distinguish it from the game as a piece of digital media. Designers of games for impact are, in reality and at their best, designers of big “G” Games for impact.

 

 

Semantacademy

 

Our language is missing lots of words for important things.  The absence of words often warps debates.  The current controversies over college are a good example.  
If college is a necessary good that everyone one in our society should have, then it is one thing.  If it is a status granting experience necessarily restricted to the favored few, then it is another thing.  Of course, we can have both, colleges for the many and colleges for the few.
If college is about getting a job, then it is one thing. If it is about enhancing a life, then it is another. Of course, we can have both, job training for the many and life enhancement for the few. Or even training for bad jobs for the many, training for good jobs for the few, and life enhancement for whoever is rich enough or poor enough not to care about a job as the purpose of life.
Here is a question, though:  Even when one is well and truly “trained” for a job, is there some level of “schooling” that one should/could have that has nothing to do with jobs and money and success?  If we added this level of “schooling” at the end of the job training level, would it just eventually become another level that everyone needed in order to get a job or get along in society, perhaps because we had devalued earlier levels of schooling/training because everyone now had them?
Let’s imagine a group of people coming together to explore the meanings of things, the meanings of life, society, humans, the natural world, and all they contain.  Some are “professors” who passionately profess their views on the meanings of things so “students” can compare and contrast them and come up with their own passions.  The basic rules are: evidence counts; things are not true just because you say them; and you have to be brave enough to change your mind even when it makes you uncomfortable.
Because exploring the meanings of things does not necessarily lead to anything useful or financially rewarding, it might end up open only to those with the resources to save them from “real work”.  It would then give status and soon people would care more about the status than the thing.
If professors were paid more for espousing some things and not others, their views would be warped.  It would no longer be passion, but rather profit, that fuelled them.
It is clear that the “explore the meanings of things” enterprise cannot exist if profit or status is strongly at play in the enterprise.  The enterprise to be valuable would have to be “worthless” in the sense of not being a matter of profit or status.
The ancient university avoided profit and status by being religious and claiming that Truth and Beauty were akin to God.  People could be excused for doing worthless things because they were doing things of “higher worth”.  Alas, exploring things led to an exploration of religion itself, an exploration that eventually scared the sponsors off.
Asking what Emily Dickenson meant will bring one no profit or status (anymore).  Asking what the bible meant will bring one no profit or status, but perhaps some grief from others.  Asking why anyone would ever think a corporation was a person will bring no profit or status, but perhaps some despair or maybe even activism.  But the point of the enterprise is not what it will bring or not.  The point is to enlarge the semantics of the human mind and of human society, something that does not necessarily bring happiness or joy.  The point is a larger vocabulary.  The enterprise is about “language”.
It bothers people—conservatives and liberals alike—that some activity could have no point other than some people are impassioned to do it because it feels good, right, and necessary.  But lots of things in life have no point, most things in fact. 
So what should we call this “worthless enterprise”?  It is not a college as we know it, certainly not now, if ever, though it was the dream of some.  It is not something everyone wants or even believes could exist.  The Internet has allowed such “worthless enterprises” to arise among impassioned groups going it on their own, though they don’t always follow the basic rules.  
We have no name. I will call it a “semantacademy”, a place to follow some basic rules for finding and making meaning, little lights in the dark, and connections among things and people.  It brings no profit or status to know the javelina breaking into my garage to get the bird seed is not a pig.  I just think it would be wrong not to know.  For me it shows respect for the javelina, though I adore pigs as well.  Some people want to hunt the javlina, others to enjoy him with no name.  I want to revel in his new world presence, imaging him cavorting with the mega-fauna we once had.  De gustibus…

Our language is missing lots of words for important things.  The absence of words often warps debates.  The current controversies over college are a good example.  

If college is a necessary good that everyone in our society should have, then it is one thing.  If it is a status granting experience necessarily restricted to the favored few, then it is another thing.  Of course, we can have both, colleges for the many and colleges for the few.

If college is about getting a job, then it is one thing. If it is about enhancing a life, then it is another. Of course, we can have both, job training for the many and life enhancement for the few. Or even training for bad jobs for the many, training for good jobs for the few, and life enhancement for whoever is rich enough or poor enough not to care about a job as the purpose of life.

Here is a question, though:  Even when one is well and truly “trained” for a job, is there some level of “schooling” that one should/could have that has nothing to do with jobs and money and success?  If we added this level of “schooling” at the end of the job training level, would it just eventually become another level that everyone needed in order to get a job or get along in society, perhaps because we had devalued earlier levels of schooling/training because everyone now had them?

Let’s imagine a group of people coming together to explore the meanings of things, the meanings of life, society, humans, the natural world, and all they contain.  Some are “professors” who passionately profess their views on the meanings of things so “students” can compare and contrast them and come up with their own passions.  The basic rules are: evidence counts; things are not true just because you say them; and you have to be brave enough to change your mind even when it makes you uncomfortable.

Because exploring the meanings of things does not necessarily lead to anything useful or financially rewarding, it might end up open only to those with the resources to save them from “real work”.  It would then give status and soon people would care more about the status than the thing.

If professors were paid more for espousing some things and not others, their views would be warped.  It would no longer be passion, but rather profit, that fuelled them.

It is clear that the “explore the meanings of things” enterprise cannot exist if profit or status is strongly at play in the enterprise.  The enterprise to be valuable would have to be “worthless” in the sense of not being a matter of profit or status.

The ancient university avoided profit and status by being religious and claiming that Truth and Beauty were akin to God.  People could be excused for doing worthless things because they were doing things of “higher worth”.  Alas, exploring things led to an exploration of religion itself, an exploration that eventually scared the sponsors off.

Asking what Emily Dickinson meant will bring one no profit or status (anymore).  Asking what the bible meant will bring one no profit or status, but perhaps some grief from others.  Asking why anyone would ever think a corporation was a person will bring no profit or status, but perhaps some despair or maybe even activism.  But the point of the enterprise is not what it will bring or not.  The point is to enlarge the semantics of the human mind and of human society, something that does not necessarily bring happiness or joy.  The point is a larger vocabulary.  The enterprise is about “language”.

It bothers people—conservatives and liberals alike—that some activity could have no point other than some people are impassioned to do it because it feels good, right, and necessary.  But lots of things in life have no point, most things in fact. 

So what should we call this “worthless enterprise”?  It is not a college as we know it, certainly not now, if ever, though it was the dream of some.  It is not something everyone wants or even believes could exist.  The Internet has allowed such “worthless enterprises” to arise among impassioned groups going it on their own, though they don’t always follow the basic rules.  

We have no name. I will call it a “semantacademy”, a place to follow some basic rules for finding and making meaning, little lights in the dark, and connections among things and people.  It brings no profit or status to know the javelina breaking into my garage to get the bird seed is not a pig.  I just think it would be wrong not to know.  For me it shows respect for the javelina, though I adore pigs as well.  Some people want to hunt the javelina, others to enjoy him with no name.  I want to revel in his ancient New World presence, imaging him cavorting with the mega-fauna we once had.  De gustibus…

 

 

 

Literacy: From Writing to Fabbing

 

Oral language is a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code maps ideas (concepts) to (real or imagined) things via words and grammar.  Oral language evolved in human beings and all human languages have deep commonalities.  All humans, barring serious problems, gain a native language and can both produce (speak) and consume (listen) it well.  Barring illness, there are no people who can listen but not speak or who fail to master relative clauses, say.  Oral language is not an invention that some cultures discovered and others did not.  In that sense, it is not an invention at all.  It is a human trait.  
Oral language has one signal weakness.  Speech is transitory; it dies almost as soon as it is produced. Writing systems were invented to mitigate this weakness.  States and institutions, which necessarily must reach across time and space, could not exist without writing.
Writing systems are cultural inventions.  Writing is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to (real or imagined) things via written symbols, symbols more permanent that spoken words.  Writing came on the scene long after oral language had evolved and is a relatively recent invention.  Few cultures have historically created a writing system, though many have borrowed one.  
Writing systems are cultural inventions.  Some writing systems are closely tied to speech (e.g., alphabets) and others are not (e.g., logograms).  Unlike speech, in the case of writing systems, production (writing) is less common and more restricted than is consumption (reading).  It is normal for people to be better at reading than writing and even the ability to read has rarely been universal in societies.  The ability to write has never been.
There are no social gaps in terms of race, class, or gender in oral language as it first evolved, though we will see below that social groups, often in tandem with writing, have created forms of oral language which do give rise to gaps.  Everyone speaks and hears the vernacular of their native language just fine, albeit in terms of different dialects.  No one needs to be overtly taught their native language.  It is acquired through normal social interactions with primary caregivers.  
On the other hand, literacy regularly gives rise to social gaps where some groups have less access to or skill in certain forms of writing or reading than do others.  Often these gaps reflect status and the distribution of power or wealth in society.  All people need to be taught literacy in the sense that the environment must be arranged in certain special ways to ensure its acquisition.  Every child learns his or her native language equally well at home, regardless of home-based differences, but reading and writing (especially of the sorts that make for success in school) are very sensitive to early home-based factors in how and how well they are acquired.
Writing systems almost always give rise to specialized forms of oral language, sometimes called “registers” by linguists.  These are things like the language of law, physics, mathematics, or game design.  These registers extend oral language to carry out special functions or activities that not all societies may have.  They create a certain division of labor in terms of language.  Registers create social gaps because they require access to the specialized social groups or institutions that use them.  They also require skill with the functions the register is used to carry out and very often with the written forms of language that are also connected to these functions.
Oral language—a gift nearly all humans have—is, in reality, a set of design tools.  All humans when they speak are designers.  They organize words and phrases into patterns that will communicate not just information but effects of all different sorts.  In fact, grammar can be seen as a design kit, full of tools with which to make meanings and effects, just like media of any sort.  Human inequality starts when design kits are not open to all and literacy is one such design kit.  In the case of such non-“open source” design kits, production is far less prevalent than consumption and, thus, design is restricted.  A few people are “priests” and the rest are “laity”.  This, in fact, has been the history of writing and reading.
Literacy is multiple in the sense that there are different ways of writing and reading fit for and used for different functions.  Therefore, no one is universally literate.  There are, for all of us, forms of writing and reading, and their accompanying registers, that we have not mastered.  A person may be highly literate in poetry, but illiterate in physics, and vice versa.  In these respects we all are both literate and illiterate.  
Thus, it is problematic defining literacy as reading and writing—however obvious that definition may seem—because literacy requires forms of reading and writing tied to the ability to carry out different functions or activities.  And these functions or activities are often tied to registers in oral language.  A “literacy” (and there are many such “literacies”) requires ways of writing and reading, ways of doing, and ways of speaking and interacting with others.  Otherwise one is not literate in that way.  This is also why teaching literacy without teaching doing and teaching registers (specialist ways of speaking and interacting to carry out special functions) does not work well, especially for closing social gaps.
Writing, of course, does not replace oral language.  But writing does change the ecology or oral language.  It creates new forms of it (specialist registers), makes new demands on it, demands new skills in it, and creates new patterns of inequality.  
The term “digital literacy” is fully appropriate and not really just a metaphor.  Each digital media is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to virtual things (simulation of things) via computational computer code.  Each digital media is a design kit.  For digital media, as for writing, production is more restricted than consumption.  Different sorts and degrees of mastery are sensitive to early home based factors and digital media create social gaps.  Digital literacies are multiple in the sense that they are tied to different functions or activities and, they too, are very often accompanied by specific special registers of oral language.  They are, in many respects, just like writing and reading, i.e., what we traditionally mean by “literacy”.
So far digital literacies have created the sorts of inequalities and social gaps we associate with traditional literacy.  Higher-order, value-added forms of digital literacy—like “modding” in the case of video games—appear to be the preserve of the more privileged, as do the more sophisticated forms of writing.  Privileged young people get more access, mentoring, and modeling early in life in regard to digital literacies than less privileged children, as they do also in the case of traditional literacy.  
We have long known that school-based forms of literacy flourish in the homes of young children who have lots of mentoring, attachment parenting, and complex, sustained interactive talk with adults.  The same seems to be true with digital literacies that “pay off” in terms of success in school or in society.  In part, in both cases, such mentoring, parenting, and talk gives rise to non-cognitive skills like confidence, persistence, delayed gratification, coping with challenge, and meta-cognition that highly correlate with success in school and society, where, more and more, traditional and digital literacy interact.
Some say digital media hold out more opportunity for all people to be producers than did traditional literacy.  But writing was always potentially open to everyone, just as is production with digital media.  The real potential that digital media unleashed was the opportunity to learn out of school and to learn from a much wider array of peers and adults.  In Western society, schools have long had a monopoly on traditional literacy, but they have no such monopoly on digital literacies, though some would like to see them gain such a monopoly.  Thus, while writing still stagnates in our schools, it flourishes on fan fiction sites, facilitated by digital tools.  
Nonetheless, the use of digital media and writing on digital sites is subject to the Pareto Principle: 10 percent of the people at best make 90 percent of the contributions.  Furthermore, higher-order contributions are often restricted to a small group of aficionados.  In this sense, one danger is that digital media can simply replicate the inequalities that school creates, albeit out of school.  The fact that digital literacies have spread primarily out of school has not yet made them a real force for equality, at least in regard to their higher-order, value-added forms.
The Maker Movement opens up yet another set of design kits, another set of literacies, what we can call “maker literacies”.   Maker literacies are not new.  People have been making things like quilts and furniture at home of hundreds of years.  What is new is the proliferation of making and the ways in which everyday people can compete with businesses, experts, and industry today thanks to digital media.  The special part of the Maker Movement I want to concentrate on here is digital fabrication, what we can just call “Fab”.    Fab is the newest literacy beyond digital literacies.
Fab is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to real things via computational computer code.  
Oral language refers to things in the world.  Language is indexical in the sense that it points to or refers to things, but it cannot touch and handle them.  Things always stay just out of reach.  Digital literacies simulate things, virtual things that can be handled and transformed by the very code that produces them.  But like language, digital media cannot touch and handle real things; it can just manipulate them on a screen.
Fab makes real things.  It can handle and transform them.  It has been argued that what constituted human intelligence in the beginning was our ability to think and plan in our heads deeply prior to acting .  Digital media greatly enhanced this human trait.  Such media allow us to think and plan on screens in forms that go far beyond the powers of unaided human thought.  
Humans have always, of course, been able to make things.  Indeed, some scholars have defined humans as tool makers and homo faber.   But prior to Fab making was a one-way street. You could go from conception to construction, but not back again.  Fab makes making a two-way street.  We can now turn bits (digital code) into atoms (things) by “printing” the code and we can turn atoms into bits by reality capturing devices that digitize things and make them into digital code.  “Printing” here means machines that can add or subtract material to make things on demand from digital code.
Language and digital media are complementary.  Language is good at creating abstractions out of lived experience by finding and naming patterns in that experience.  Writing takes abstraction to its furthest extent, especially in special symbol systems like mathematics.  Digital media is good at creating new experiences or mimicking old ones.  Digital media allow us to think through external images and simulations and not just through conceptual abstractions.  One of the greatest powers of digital media is that it can allow people to have experiences that are hard for humans to have in the real world (or to have more than once), experiences that, nonetheless, words can refer to, such as being an electron or sky diving without a parachute.  Digital media can, thus, greatly enhance the ability humans have to find and name patterns in experience, the basis of language and learning.
Think of Dungeons and Dragons played as a role playing game with paper and pencil. This is traditional literacy.  Here players use words and other symbols (and the occasional plastic figures) to create images in their heads (imaginations) and in the other player’s heads.  A video game (including a D&D game like Neverwinter Nights) involves players manipulating images on a screen, not in their heads.  Imagination becomes externalized.  One is not better than the other.  They are complementary ways of thinking, learning, and problem solving.
Fab, our newest literacy, involves a code that maps from ideas to atoms (and back again) via bits.  What you can design in a computer, you can order machines (“printers” and “extractors”) to make.  What is in the world can be captured digitally (“reality capture”), put in a computer, re-designed, and “printed” back out into the world.  The atoms can be materials, cells, or chemicals.  Humans are on the verge of erasing the lines between the imaginary, the digital, and the “real” and moving effortlessly back and forth among them.  Bits no longer need to create just virtual things; they can now create real ones.  In turn, real thing can now easily become virtual ones.
The day may come where we can “print” an organ like a liver or even (the initial cellular plan for) a living thing like a dog.  As of now we can print skin, cells, cakes, and houses.  Fab is not indexical.  It doesn’t point to things.  It is not a simulation.  It does not make just virtual things.  Fab is material.  It makes and manipulates matter.  Fab trades not in concepts or simulations alone but in physical things as well.  It is the “word become flesh”, formerly the domain of magic and religion.  The ideas in our minds and the images on our screens can now be born in the world and the world can enter our minds and computers to be re-born as something new.  A whole new material form of thought and planning opens up for humans.
Fab is a set of design kits to make things into bits and bits into things.  It creates an entirely new way of writing and reading the world.  Fab will proliferate into different literacies, different ways of producing and consuming meaning for different functions, accompanied by new registers of oral language.  Fab is a cultural invention like literacy.  It will without doubt create social gaps and inequalities if we let it.
Fab is a form of literacy where production (“writing”) is the main form.  It finally reverses the polarity of traditional literacy and digital literacy, where consuming (“reading”) proliferates, but production (“writing”) does not, creating priests and laity.  To be literate in Fab you must be a maker or at least know how a digital object will translate into a real one (and vice versa).  It is as if we had demanded that to be literate in writing you had to be a writer and not just a reader, to be literate in digital game literacy, you had to be a designer and not just a player.  In fact, a culture of Fab could lead to just such demands. 
Just as writing made new demands on and demanded new skills in oral language, and digital lieracy made new demands on and demanded new skills in both oral language and written language, Fab makes new demands on and demands new skills in oral language, in literacy, and digital literacy.  The ecology of oral language, of writing, and of digital literacy—and their various combinations and integrations—will change.  Language, literacy, and digital literacy will become yet more complicated.  The social gaps in each will compound, along with whatever gaps Fab literacy creates unless we will it otherwise.
Fab could create a world with yet deeper inequalities than we currently have, a world where only a few engage in the alchemy of turning ideas into bits into atoms and back again.  The rest will live in a world where the stuff of life and the world--objects, cells, materials—are owned and operated by only a few.  Fab is a new literacy and we have as yet no real idea how it will work out.  But it is a special and, in some sense, final one.  For centuries, since Shakespeare at least, being modern has meant to fashion oneself and writing has played a massive role in this process.  Now being modern will mean to fashion ones world as the stage on which one plays and lives.  
Each new literacy ups the ante on ethical questions beyond issues of inequality.  Words can hurt and harm, we know.  Writing can greatly spread that harm.  Digital media can spread it yet faster and further.  But Fab can literally remake the world we live in, exhausting it or expanding it, destroying it or renewing it.  Fab can make and remake the very stage on which we humans act for good and ill.
How many of us will get to be homo faber?  Humans have always been the ultimate took makers.  Soon the tools for world making will be cheap enough to be in the hands of everyone, should we want to make that happen.  Will we, as a species, make a better world or a worse one when some or many or all of us become god-like creators, calling worlds into being? 

Oral language is a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code maps ideas (concepts) to (real or imagined) things via words and grammar.  Oral language evolved in human beings and all human languages have deep commonalities.  All humans, barring serious problems, gain a native language and can both produce (speak) and consume (listen) it well.  Barring illness, there are no people who can listen but not speak or who fail to master relative clauses, say.  Oral language is not an invention that some cultures discovered and others did not.  In that sense, it is not an invention at all.  It is a human trait.  

 

Oral language has one signal weakness.  Speech is transitory; it dies almost as soon as it is produced. Writing systems were invented to mitigate this weakness.  States and institutions, which necessarily must reach across time and space, could not exist without writing.

 

Writing systems are cultural inventions.  Writing is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to (real or imagined) things via written symbols, symbols more permanent that spoken words.  Writing came on the scene long after oral language had evolved and is a relatively recent invention.  Few cultures have historically created a writing system, though many have borrowed one.  

 

Writing systems are cultural inventions.  Some writing systems are closely tied to speech (e.g., alphabets) and others are not (e.g., logograms).  Unlike speech, in the case of writing systems, production (writing) is less common and more restricted than is consumption (reading).  It is normal for people to be better at reading than writing and even the ability to read has rarely been universal in societies.  The ability to write has never been.

 

There are no social gaps in terms of race, class, or gender in oral language as it first evolved, though we will see below that social groups, often in tandem with writing, have created forms of oral language which do give rise to gaps.  Everyone speaks and hears the vernacular of their native language just fine, albeit in terms of different dialects.  No one needs to be overtly taught their native language.  It is acquired through normal social interactions with primary caregivers.  

 

On the other hand, literacy regularly gives rise to social gaps where some groups have less access to or skill in certain forms of writing or reading than do others.  Often these gaps reflect status and the distribution of power or wealth in society.  All people need to be taught literacy in the sense that the environment must be arranged in certain special ways to ensure its acquisition.  Every child learns his or her native language equally well at home, regardless of home-based differences, but reading and writing (especially of the sorts that make for success in school) are very sensitive to early home-based factors in how and how well they are acquired.

 

Writing systems almost always give rise to specialized forms of oral language, sometimes called “registers” by linguists.  These are things like the language of law, physics, mathematics, or game design.  These registers extend oral language to carry out special functions or activities that not all societies may have.  They create a certain division of labor in terms of language.  Registers create social gaps because they require access to the specialized social groups or institutions that use them.  They also require skill with the functions the register is used to carry out and very often with the written forms of language that are also connected to these functions.

 

Oral language—a gift nearly all humans have—is, in reality, a set of design tools.  All humans when they speak are designers.  They organize words and phrases into patterns that will communicate not just information but effects of all different sorts.  In fact, grammar can be seen as a design kit, full of tools with which to make meanings and effects, just like media of any sort.  Human inequality starts when design kits are not open to all and literacy is one such design kit.  In the case of such non-“open source” design kits, production is far less prevalent than consumption and, thus, design is restricted.  A few people are “priests” and the rest are “laity”.  This, in fact, has been the history of writing and reading.

 

Literacy is multiple in the sense that there are different ways of writing and reading fit for and used for different functions.  Therefore, no one is universally literate.  There are, for all of us, forms of writing and reading, and their accompanying registers, that we have not mastered.  A person may be highly literate in poetry, but illiterate in physics, and vice versa.  In these respects we all are both literate and illiterate.  

 

Thus, it is problematic defining literacy as reading and writing—however obvious that definition may seem—because literacy requires forms of reading and writing tied to the ability to carry out different functions or activities.  And these functions or activities are often tied to registers in oral language.  A “literacy” (and there are many such “literacies”) requires ways of writing and reading, ways of doing, and ways of speaking and interacting with others.  Otherwise one is not literate in that way.  This is also why teaching literacy without teaching doing and teaching registers (specialist ways of speaking and interacting to carry out special functions) does not work well, especially for closing social gaps.

 

Writing, of course, does not replace oral language.  But writing does change the ecology or oral language.  It creates new forms of it (specialist registers), makes new demands on it, demands new skills in it, and creates new patterns of inequality.  

 

The term “digital literacy” is fully appropriate and not really just a metaphor.  Each digital media is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to virtual things (simulation of things) via computational computer code.  Each digital media is a design kit.  For digital media, as for writing, production is more restricted than consumption.  Different sorts and degrees of mastery are sensitive to early home based factors and digital media create social gaps.  Digital literacies are multiple in the sense that they are tied to different functions or activities and, they too, are very often accompanied by specific special registers of oral language.  They are, in many respects, just like writing and reading, i.e., what we traditionally mean by “literacy”.

 

So far digital literacies have created the sorts of inequalities and social gaps we associate with traditional literacy.  Higher-order, value-added forms of digital literacy—like “modding” in the case of video games—appear to be the preserve of the more privileged, as do the more sophisticated forms of writing.  Privileged young people get more access, mentoring, and modeling early in life in regard to digital literacies than less privileged children, as they do also in the case of traditional literacy.  

 

We have long known that school-based forms of literacy flourish in the homes of young children who have lots of mentoring, attachment parenting, and complex, sustained interactive talk with adults.  The same seems to be true with digital literacies that “pay off” in terms of success in school or in society.  In part, in both cases, such mentoring, parenting, and talk gives rise to non-cognitive skills like confidence, persistence, delayed gratification, coping with challenge, and meta-cognition that highly correlate with success in school and society, where, more and more, traditional and digital literacy interact.

 

Some say digital media hold out more opportunity for all people to be producers than did traditional literacy.  But writing was always potentially open to everyone, just as is production with digital media.  The real potential that digital media unleashed was the opportunity to learn out of school and to learn from a much wider array of peers and adults.  In Western society, schools have long had a monopoly on traditional literacy, but they have no such monopoly on digital literacies, though some would like to see them gain such a monopoly.  Thus, while writing still stagnates in our schools, it flourishes on fan fiction sites, facilitated by digital tools.  

 

Nonetheless, the use of digital media and writing on digital sites is subject to the Pareto Principle: 10 percent of the people at best make 90 percent of the contributions.  Furthermore, higher-order contributions are often restricted to a small group of aficionados.  In this sense, one danger is that digital media can simply replicate the inequalities that school creates, albeit out of school.  The fact that digital literacies have spread primarily out of school has not yet made them a real force for equality, at least in regard to their higher-order, value-added forms.

 

The Maker Movement opens up yet another set of design kits, another set of literacies, what we can call “maker literacies”.   Maker literacies are not new.  People have been making things like quilts and furniture at home of hundreds of years.  What is new is the proliferation of making and the ways in which everyday people can compete with businesses, experts, and industry today thanks to digital media.  The special part of the Maker Movement I want to concentrate on here is digital fabrication, what we can just call “Fab”.    Fab is the newest literacy beyond digital literacies.

 

Fab is also a code that allows humans to produce and consume meanings interactively and to engage in joint activities.  The code is a mapping from ideas (concepts) to real things via computational computer code.  

 

Oral language refers to things in the world.  Language is indexical in the sense that it points to or refers to things, but it cannot touch and handle them.  Things always stay just out of reach.  Digital literacies simulate things, virtual things that can be handled and transformed by the very code that produces them.  But like language, digital media cannot touch and handle real things; it can just manipulate them on a screen.

 

Fab makes real things.  It can handle and transform them.  It has been argued that what constituted human intelligence in the beginning was our ability to think and plan in our heads deeply prior to acting .  Digital media greatly enhanced this human trait.  Such media allow us to think and plan on screens in forms that go far beyond the powers of unaided human thought.  

 

Humans have always, of course, been able to make things.  Indeed, some scholars have defined humans as tool makers and homo faber.   But prior to Fab making was a one-way street. You could go from conception to construction, but not back again.  Fab makes making a two-way street.  We can now turn bits (digital code) into atoms (things) by “printing” the code and we can turn atoms into bits by reality capturing devices that digitize things and make them into digital code.  “Printing” here means machines that can add or subtract material to make things on demand from digital code.

 

Language and digital media are complementary.  Language is good at creating abstractions out of lived experience by finding and naming patterns in that experience.  Writing takes abstraction to its furthest extent, especially in special symbol systems like mathematics.  Digital media is good at creating new experiences or mimicking old ones.  Digital media allow us to think through external images and simulations and not just through conceptual abstractions.  One of the greatest powers of digital media is that it can allow people to have experiences that are hard for humans to have in the real world (or to have more than once), experiences that, nonetheless, words can refer to, such as being an electron or sky diving without a parachute.  Digital media can, thus, greatly enhance the ability humans have to find and name patterns in experience, the basis of language and learning.

 

Think of Dungeons and Dragons played as a role playing game with paper and pencil. This is traditional literacy.  Here players use words and other symbols (and the occasional plastic figures) to create images in their heads (imaginations) and in the other player’s heads.  A video game (including a D&D game like Neverwinter Nights) involves players manipulating images on a screen, not in their heads.  Imagination becomes externalized.  One is not better than the other.  They are complementary ways of thinking, learning, and problem solving.

 

Fab, our newest literacy, involves a code that maps from ideas to atoms (and back again) via bits.  What you can design in a computer, you can order machines (“printers” and “extractors”) to make.  What is in the world can be captured digitally (“reality capture”), put in a computer, re-designed, and “printed” back out into the world.  The atoms can be materials, cells, or chemicals.  Humans are on the verge of erasing the lines between the imaginary, the digital, and the “real” and moving effortlessly back and forth among them.  Bits no longer need to create just virtual things; they can now create real ones.  In turn, real thing can now easily become virtual ones.

 

The day may come where we can “print” an organ like a liver or even (the initial cellular plan for) a living thing like a dog.  As of now we can print skin, cells, cakes, and houses.  Fab is not indexical.  It doesn’t point to things.  It is not a simulation.  It does not make just virtual things.  Fab is material.  It makes and manipulates matter.  Fab trades not in concepts or simulations alone but in physical things as well.  It is the “word become flesh”, formerly the domain of magic and religion.  The ideas in our minds and the images on our screens can now be born in the world and the world can enter our minds and computers to be re-born as something new.  A whole new material form of thought and planning opens up for humans.

 

Fab is a set of design kits to make things into bits and bits into things.  It creates an entirely new way of writing and reading the world.  Fab will proliferate into different literacies, different ways of producing and consuming meaning for different functions, accompanied by new registers of oral language.  Fab is a cultural invention like literacy.  It will without doubt create social gaps and inequalities if we let it.

 

Fab is a form of literacy where production (“writing”) is the main form.  It finally reverses the polarity of traditional literacy and digital literacy, where consuming (“reading”) proliferates, but production (“writing”) does not, creating priests and laity.  To be literate in Fab you must be a maker or at least know how a digital object will translate into a real one (and vice versa).  It is as if we had demanded that to be literate in writing you had to be a writer and not just a reader, to be literate in digital game literacy, you had to be a designer and not just a player.  In fact, a culture of Fab could lead to just such demands. 

 

Just as writing made new demands on and demanded new skills in oral language, and digital lieracy made new demands on and demanded new skills in both oral language and written language, Fab makes new demands on and demands new skills in oral language, in literacy, and digital literacy.  The ecology of oral language, of writing, and of digital literacy—and their various combinations and integrations—will change.  Language, literacy, and digital literacy will become yet more complicated.  The social gaps in each will compound, along with whatever gaps Fab literacy creates unless we will it otherwise.

 

Fab could create a world with yet deeper inequalities than we currently have, a world where only a few engage in the alchemy of turning ideas into bits into atoms and back again.  The rest will live in a world where the stuff of life and the world--objects, cells, materials—are owned and operated by only a few.  Fab is a new literacy and we have as yet no real idea how it will work out.  But it is a special and, in some sense, final one.  For centuries, since Shakespeare at least, being modern has meant to fashion oneself and writing has played a massive role in this process.  Now being modern will mean to fashion ones world as the stage on which one plays and lives.  

 

Each new literacy ups the ante on ethical questions beyond issues of inequality.  Words can hurt and harm, we know.  Writing can greatly spread that harm.  Digital media can spread it yet faster and further.  But Fab can literally remake the world we live in, exhausting it or expanding it, destroying it or renewing it.  Fab can make and remake the very stage on which we humans act for good and ill.

 

How many of us will get to be homo faber?  Humans have always been the ultimate took makers.  Soon the tools for world making will be cheap enough to be in the hands of everyone, should we want to make that happen.  Will we, as a species, make a better world or a worse one when some or many or all of us become god-like creators, calling worlds into being? 

 

 

 

 

 

 

 

 

Big Experience

 

BIG EXPERIENCE
I have written a lot about experience.
We used to think that the mind was made of rules and calculations.
But it is made first and foremost of patterns found in lived experience.
We use these patterns as bets and guides for future decisions and actions.
The old scout sits in the stands.
“I’ve done this for 30 years”.
“I know’em when I see ‘em”.
“That guy’s a keeper”.
Now a quant runs some numbers.
Numbers originally dreamed up by amateur baseball fanatics.
The numbers say he’s not a keeper.
And he’s not.
Alan Greenspan says “I’ve been doing this for 40 years”.
“I’ve run this economy for a long time”.
“I know my markets”.
“I know business and business is the business of America”.
The global economy tanked in 2008, thanks to Al and US.
Alan said “I never saw it coming”.
In fact, he had advised people to trade in their fixed mortgages for balloon payments.
He had said the price of houses would never fall.  
Alan went to Congress after the collapse.
“Nothing in my 40 years of economics told me this would happen”.
“I believed that free markets always give rise to the best outcomes”.
“I believed CEOs would never purposely harm the companies they run”.
But Alan! There were no free markets.
You deregulated them.
Frost said you cannot plan tennis without a net.
Alan, you removed the referees and were surprised the thugs cheated.
But Alan!  The CEO’s companies were “companies” no more.
You thought a company made something that made profit.
But now companies are just holds for quick bets on their stock price.
Bet now and get out quick before customers find out no one cares what the company makes.
The quant guys with their Big Data ran the numbers.
Alan, they knew it was a House of Cards and it was all going to fall.
The smart guys on the Street took the short bets and got vastly richer yet.
The “little” guys saw their houses, families, and lives blow away.
Karl Rove fell apart on Fox News when Ohio was called for Obama.
“It can’t be so”, he said.
“I’ve done this for many many years”.  
“I was Bush’s Brain”.
“I know there are Red Votes still out there.  I just know it”.
But Karl missed the Puerto Ricans moving into the Red county in Florida.
He missed demographic changes that had been predicted and in motion since the 1970’s.
He missed facts of human nature:
Trying to stop people from doing something (i.e., voting) makes them want to do it more. 
Insulting people doesn’t make them want to vote for you.
You can’t buy votes unless you buy the voters.  
Money to ad companies and television channels won’t cut it.
And you don’t buy the voters by knocking down their wages.
The quant guys ran their algorithms and massaged their data seven ways to Sunday.
They said here is how the election will go.
And that is just how it went.
And the people on Fox looked like someone had killed their dog.
Nate Silver called the election.
He had started as an amateur baseball stats guy.
Numbers are dangerous, of course.
Algorithms on computers now buy and sell stocks on the fly at warp speed.
There is the danger they will all get in synch and sink the market.
Getting in synch is what complex systems often do, like fireflies.
But numbers are benignly indifferent, too.
They don’t care that the catcher is bald.
They don’t care that Puerto Ricans moved in.
They don’t care that the Alan and Karl are powerful, elite, old, and sad.
Numbers are humane or, at least, tolerant.
The problem is that experience isn’t what it used to be.
Experts are people with credentials who have had lots of experience.
But even a vast amount of experience is a small sample in the face of Big Data.
And credentials are for being good at one narrow thing.
Yet the important stuff today is all about many complex interactions. 
Today, the expert’s one thing is soon gone or vastly changed anyway.
Furthermore, amateurs on the Web can now beat experts at their own game.
But, alas, experience is the foundation of human learning and intelligence.
We build our knowledge on the basis of patterns we have found in our experience.
We make our choices on the basis of patterns we have found in our experience.
No experience, no knowledge—we are left with only words floating free from the world.
But now that Big Data trumps experience, we can all look like someone killed our dog.
Big Data can level the proud and humble alike.
But numbers have their limits.
They can predict what will happen, 
But they cannot say what should happen.
To trump Big Data—to tame it for the good—we need Big Experience.
Yours and mine alone will no longer do.
We need to pool our experiences.
To get diverse minds and souls in synch, like fireflies.
To make everyone count.
To seek out the mutant, the odd man out.
To find the datum Big Data will never find,
Because it is just the odd thing one person saw or felt, 
A thing too small to see and too big to miss.
On the savannah, as we evolved, human experience was usually veridical because the world was small.
But today our world is big and out experiences of it is small and limited.
Our unaided minds—no matter how expert we are—are no good anymore.
Big Data will always show us the world does not fit our preconceptions.
But Big Data will face the same problem the Social Sciences have always faced.
Humans can make things true by willing and doing them.
They can change the Data.
Unlike an atom they pay attention to what is said about them.
The question is: What should we make?
We can make more than ever before with Fab Labs soon to be as prevalent as computers at home.
We can make change through networks and social media outside the strictures of institutions.
We will soon be able to make worlds as easily as we can now destroy them.
But what will we make?
Will we save the planet only to make hell on earth, perhaps even by trying to make heaven on earth?
When you can make Karl Rove cry, what will you do next?
Collective intelligence
Wisdom of the crowds
Crowd Sourcing
Synchronized Minds
Shared Minds
Networked Intelligence
Distributed Intelligence
It’s all Big Experience, the mental analogue of Big Data
Let’s hope it is wiser than our savannah minds have been.

I have written a lot about experience.

We used to think that the mind was made of rules and calculations.

But it is made first and foremost of patterns found in lived experience.

We use these patterns as bets and guides for future decisions and actions.

 

The old scout sits in the stands.

“I’ve done this for 30 years”.

“I know’em when I see ‘em”.

“That guy’s a keeper”.

 

Now a quant runs some numbers.

Numbers originally dreamed up by amateur baseball fanatics.

The numbers say he’s not a keeper.

And he’s not.

 

Alan Greenspan says “I’ve been doing this for 40 years”.

“I’ve run this economy for a long time”.

“I know my markets”.

“I know business and business is the business of America”.

 

The global economy tanked in 2008, thanks to Al and US.

Alan said “I never saw it coming”.

In fact, he had advised people to trade in their fixed mortgages for balloon payments.

He had said the price of houses would never fall.  

 

Alan went to Congress after the collapse.

“Nothing in my 40 years of economics told me this would happen”.

“I believed that free markets always give rise to the best outcomes”.

“I believed CEOs would never purposely harm the companies they run”.

 

But Alan! There were no free markets.

You deregulated them.

Frost said you cannot play tennis without a net.

Alan, you removed the referees and were surprised the thugs cheated.

 

But Alan!  The CEO’s companies were “companies” no more.

You thought a company made something that made profit.

But now companies are just holds for quick bets on their stock price.

Bet now and get out quick before customers find out no one cares what the company makes.

 

The quant guys with their Big Data ran the numbers.

Alan, they knew it was a House of Cards and it was all going to fall.

The smart guys on the Street took the short bets and got vastly richer yet.

The “little” guys saw their houses, families, and lives blow away.

 

Karl Rove fell apart on Fox News when Ohio was called for Obama.

“It can’t be so”, he said.

“I’ve done this for many many years”.  

“I was Bush’s Brain”.

“I know there are Red Votes still out there.  I just know it”.

 

But Karl missed the Puerto Ricans moving into the Red county in Florida.

He missed demographic changes that had been predicted and in motion since the 1970’s.

He missed facts of human nature:

Trying to stop people from doing something (i.e., voting) makes them want to do it more. 

Insulting people doesn’t make them want to vote for you.

You can’t buy votes unless you buy the voters.  

Money to ad companies and television channels won’t cut it.

And you don’t buy the voters by knocking down their wages.

 

The quant guys ran their algorithms and massaged their data seven ways to Sunday.

They said here is how the election will go.

And that is just how it went.

And the people on Fox looked like someone had killed their dog.

Nate Silver called the election.

He had started as an amateur baseball stats guy.

 

Numbers are dangerous, of course.

Algorithms on computers now buy and sell stocks on the fly at warp speed.

There is the danger they will all get in synch and sink the market.

Getting in synch is what complex systems often do, like fireflies.

 

But numbers are benignly indifferent, too.

They don’t care that the catcher is bald.

They don’t care that Puerto Ricans moved in.

They don’t care that the Alan and Karl are powerful, elite, old, and sad.

Numbers are humane or, at least, tolerant.

 

The problem is that experience isn’t what it used to be.

Experts are people with credentials who have had lots of experience.

But even a vast amount of experience is a small sample in the face of Big Data.

And credentials are for being good at one narrow thing.

Yet the important stuff today is all about many complex interactions. 

Today, the expert’s one thing is soon gone or vastly changed anyway.

Furthermore, amateurs on the Web can now beat experts at their own game.

 

But, alas, experience is the foundation of human learning and intelligence.

We build our knowledge on the basis of patterns we have found in our experience.

We make our choices on the basis of patterns we have found in our experience.

No experience, no knowledge—we are left with only words floating free from the world.

But now that Big Data trumps experience, we can all look like someone killed our dog.

 

Big Data can level the proud and humble alike.

But numbers have their limits.

They can predict what will happen, 

But they cannot say what should happen.

 

To trump Big Data—to tame it for the good—we need Big Experience.

Yours and mine alone will no longer do.

We need to pool our experiences.

To get diverse minds and souls in synch, like fireflies.

To make everyone count.

To seek out the mutant, the odd man out.

To find the datum Big Data will never find,

Because it is just the odd thing one person saw or felt, 

A thing too small to see and too big to miss.

 

On the savannah, as we evolved, human experience was usually veridical because the world was small.

But today our world is big and out experiences of it is small and limited.

Our unaided minds—no matter how expert we are—are no good anymore.

Big Data will always show us the world does not fit our preconceptions.

 

But Big Data will face the same problem the Social Sciences have always faced.

Humans can make things true by willing and doing them.

They can change the Data.

Unlike an atom they pay attention to what is said about them.

 

The question is: What should we make?

We can make more than ever before with Fab Labs soon to be as prevalent as computers at home.

We can make change through networks and social media outside the strictures of institutions.

We will soon be able to make worlds as easily as we can now destroy them.

But what will we make?

Will we save the planet only to make hell on earth, perhaps even by trying to make heaven on earth?

When you can make Karl Rove cry, what will you do next?

 

Collective Intelligence

Wisdom of the Crowd

Crowd Sourcing

Synchronized Minds

Shared Minds

Networked Intelligence

Distributed Intelligence

It’s all Big Experience, the mental analogue of Big Data

Let’s hope it is wiser than our savannah minds have been.

 

 

10 Truths About Books and What They Have to Do With Video Games

Lots of people these days -- some old, some young; some in suits, some not -- are advocating that we use video games for learning, education, health, social change, and other "non-entertainment" purposes. However, lots of people who understand games, don't understand books and lots of people who understand books, don't understand games. There are 10 key truths we know about books. They happen to be equally true of other "meaning making technologies" like television and video games. Thus, in these 10 ways, books and video games are the same. They are both tools suited for certain jobs and best used in certain ways. So here are the 10 truths (for citations to the literature, see my book Situated Language and Learning, Routledge, 2004):

 1.  Books are a powerful technology. They can lead to aggression and violence (witness the Bible, the Koran, and the Turner Diaries in the wrong hands). Nazi Germany was a highly literate society. Games, so far, do not have this much power, but some day they may.

 2.   Books can lead to peace, tolerance, and charity if (and only if) they are read in a society and in families devoted to peace, tolerance, and charity.

 3.  For good learning, books require talk and social interaction with others around interpretation and implications.

 4.  Books can make you stupid by not questioning what they say.

 5.   Books can make you smart by supplying vicarious experience, new ideas, and something to debate and think about.

 6.   Books are often best used as tools for problem solving, not just in and for themselves.

 7.   To get the most out of them, books require the reader to read like a "writer" (a type of designer).

 8.   Just giving people books does not make them smarter; it all depends on what they do with them and who they do it with. For young people, it depends, too, on how much and how well they get mentored. Mentoring is, in fact, crucial.

 9.  Connecting books to the real world and to other media is good for learning, not doing so is bad for learning.

 10.  Books tend to make the "rich" richer and the poor "poorer" (those who read more in the right way get to be better and better readers and get more and more out of reading; those who don't, get to be poorer and poorer readers and get less and less out of reading. The former get more successful, the latter, less). This is called "the Matthew Principle."

 However, games do have some special properties that set them aside from books (and books have special properties that set them aside from games). Some of these are:

 1.  Games are based not on content, but on problems to solve. The content of a game (what it is "about") exists to serve problem solving.

 2.  Games can lead to more than thinking like a designer; they can lead to designing, since players can "mod" many games, i.e., use software that comes with the game to modify it or redesign it.

 3. Gamers co-author the games they play by the choices they make and how they choose to solve problems, since what they do can affect the course and sometimes the outcome of the game.

 4. Games are most often played socially and involve collaboration and competition.

 

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