How to Prepare for an Automated Future


Sebastian Thrun, left, the co-founder of Udacity, which provides online courses, recording for a programming class with Andy Brown, a course manager. Experts say online courses will be essential for workers to remain qualified as more tasks become automated. CreditMax Whittaker for The New York Times

We don’t know how quickly machines will displace people’s jobs, or how many they’ll take, but we know it’s happening — not just to factory workers but also to money managers, dermatologists and retail workers.

The logical response seems to be to educate people differently, so they’re prepared to work alongside the robots or do the jobs that machines can’t. But how to do that, and whether training can outpace automation, are open questions.

Pew Research Center and Elon University surveyed 1,408 people who work in technology and education to find out if they think new schooling will emerge in the next decade to successfully train workers for the future. Two-thirds said yes; the rest said no. Following are questions about what’s next for workers, and answers based on the survey responses.

How do we educate people for an automated world?

People still need to learn skills, the respondents said, but they will do that continuously over their careers. In school, the most important thing they can learn is how to learn.

At universities, “people learn how to approach new things, ask questions and find answers, deal with new situations,” wrote Uta Russmann, a professor of communications at the FHWien University of Applied Sciences in Vienna. “All this is needed to adjust to ongoing changes in work life. Special skills for a particular job will be learned on the job.”

Schools will also need to teach traits that machines can’t yet easily replicate, like creativity, critical thinking, emotional intelligence, adaptability and collaboration. The problem, many respondents said, is that these are not necessarily easy to teach.

“Many of the ‘skills’ that will be needed are more like personality characteristics, like curiosity, or social skills that require enculturation to take hold,” wrote Stowe Boyd, managing director of Another Voice, which provides research on the new economy.

Can we change education fast enough to outpace the machines?

About two-thirds of the respondents thought it could be done in the next decade; the rest thought that education reform takes too much time, money and political will, and that automation is moving too quickly.

“I have complete faith in the ability to identify job gaps and develop educational tools to address those gaps,” wrote Danah Boyd, a principal researcher at Microsoft Research and founder of Data and Society, a research institute. “I have zero confidence in us having the political will to address the socioeconomic factors that are underpinning skill training.”

Andrew Walls, managing vice president at Gartner, wrote, “Barring a neuroscience advance that enables us to embed knowledge and skills directly into brain tissue and muscle formation, there will be no quantum leap in our ability to ‘up-skill’ people.”

Will college degrees still be important?

College is more valuable than ever, research shows. The jobs that are still relatively safe from automation require higher education, as well as interpersonal skills fostered by living with other students.

“Human bodies in close proximity to other human bodies stimulate real compassion, empathy, vulnerability and social-emotional intelligence,” said Frank Elavsky, data and policy analyst at Acumen, a policy research firm.

But many survey respondents said a degree was not enough — or not always the best choice, especially given its price tag. Many of them expect more emphasis on certificates or badges, earned from online courses or workshops, even for college graduates.

One potential future, said David Karger, a professor of computer science at M.I.T., would be for faculty at top universities to teach online and for mid-tier universities to “consist entirely of a cadre of teaching assistants who provide support for the students.”

Employers will also place more value on on-the-job learning, many respondents said, such as apprenticeships or on-demand trainings at workplaces. Portfolios of work are becoming more important than résumés.

“Résumés simply are too two-dimensional to properly communicate someone’s skill set,” wrote Meryl Krieger, a career specialist at Indiana University. “Three-dimensional materials — in essence, job reels that demonstrate expertise — will be the ultimate demonstration of an individual worker’s skills.”

What can workers do now to prepare?

Consider it part of your job description to keep learning, many respondents said — learn new skills on the job, take classes, teach yourself new things.

Focus on learning how to do tasks that still need humans, said Judith Donath of Harvard’s Berkman Klein Center for Internet & Society: teaching and caregiving; building and repairing; and researching and evaluating.

The problem is that not everyone is cut out for independent learning, which takes a lot of drive and discipline. People who are suited for it tend to come from privileged backgrounds, with a good education and supportive parents, said Beth Corzo-Duchardt, a media historian at Muhlenberg College. “The fact that a high degree of self-direction may be required in the new work force means that existing structures of inequality will be replicated in the future,” she said.

Even if we do all these things, will there be enough jobs?

Jonathan Grudin, a principal researcher at Microsoft, said he was optimistic about the future of work as long as people learned technological skills: “People will create the jobs of the future, not simply train for them, and technology is already central.”

But the third of respondents who were pessimistic about the future of education reform said it won’t matter if there are no jobs to train for.

“The ‘jobs of the future’ are likely to be performed by robots,” said Nathaniel Borenstein, chief scientist at Mimecast, an email company. “The question isn’t how to train people for nonexistent jobs. It’s how to share the wealth in a world where we don’t need most people to work.”

Learning to Think Like a Computer


A kindergartner organizes blocks into a sequence of commands at the Eliot-Pearson Children’s School at Tufts University. CreditCharlie Mahoney for The New York Times

In “The Beauty and Joy of Computing,” the course he helped conceive for nonmajors at the University of California, Berkeley, Daniel Garcia explains an all-important concept in computer science — abstraction — in terms of milkshakes.

“There is a reason when you go to the ‘Joy of Cooking’ and you want to make a strawberry milkshake, you don’t look under ‘strawberry milkshake,’ ” he said. Rather, there is a recipe for milkshakes that instructs you to add ice cream, milk and fruit of your choice. While earlier cookbooks may have had separate recipes for strawberry milkshakes, raspberry milkshakes and boysenberry milkshakes, eventually, he imagines, someone said, “Why don’t we collapse that into one milkshake recipe?”

“The idea of abstraction,” he said, “is to hide the details.” It requires recognizing patterns and distilling complexity into a precise, clear summary. It’s like the countdown to a space launch that runs through a checklist — life support, fuel, payload — in which each check represents perhaps 100 checks that have been performed.

Concealing layers of information makes it possible to get at the intersections of things, improving aspects of a complicated system without understanding and grappling with each part. Abstraction allows advances without redesigning from scratch.

It is a cool and useful idea that, along with other cool and useful computer science ideas, has people itching to know more. It’s obvious that computers have become indispensable problem-solving partners, not to mention personal companions. But it’s suddenly not enough to be a fluent user of software interfaces. Understanding what lies behind the computer’s seeming magic now seems crucial. In particular, “computational thinking” is captivating educators, from kindergarten teachers to college professors, offering a new language and orientation to tackle problems in other areas of life.

This promise — as well as a job market hungry for coding — has fed enrollments in classes like the one at Berkeley, taken by 500 students a year. Since 2011, the number of computer science majors has more than doubled, according to the Computing Research Association. At Stanford, Princeton and Tufts, computer science is now the most popular major. More striking, though, is the appeal among nonmajors. Between 2005 and 2015, enrollment of nonmajors in introductory, mid- and upper-level computer science courses grew by 177 percent, 251 percent and 143 percent, respectively.

In the fall, the College Board introduced a new Advanced Placement course, Computer Science Principles, focused not on learning to code but on using code to solve problems. And WGBH, the PBS station in Boston, is using National Science Foundation money to help develop a program for 3- to 5-year-olds in which four cartoon monkeys get into scrapes and then “get out of the messes by applying computational thinking,” said Marisa Wolsky, executive producer of children’s media. “We see it as a groundbreaking curriculum that is not being done yet.”

Computational thinking is not new. Seymour Papert, a pioneer in artificial intelligence and an M.I.T. professor, used the term in 1980 to envision how children could use computers to learn. But Jeannette M. Wing, in charge of basic research at Microsoft and former professor at Carnegie Mellon, gets credit for making it fashionable. In 2006, on the heels of the dot-com bust and plunging computer science enrollments, Dr. Wing wrote a trade journal piece, “Computational Thinking.” It was intended as a salve for a struggling field.

“Things were so bad that some universities were thinking of closing down computer science departments,” she recalled. Some now consider her article a manifesto for embracing a computing mind-set.

Like any big idea, there is disagreement about computational thinking — its broad usefulness as well as what fits in the circle. Skills typically include recognizing patterns and sequences, creating algorithms, devising tests for finding and fixing errors, reducing the general to the precise and expanding the precise to the general.

It requires reframing research, said Shriram Krishnamurthi, a computer science professor at Brown, so that “instead of formulating a question to a human being, I formulate a question to a data set.” For example, instead of asking if the media is biased toward liberals, pose the question as: Are liberals identified as liberal in major newspapers more often or less often than conservatives are identified as conservative?

Dr. Krishnamurthi helped create “Introduction to Computation for the Humanities and Social Sciences” more than a decade ago because he wanted students “early in their undergrad careers to learn a new mode of thinking that they could take back to their discipline.” Capped at 20 students, the course now has a waitlist of more than 100.

Just as Charles Darwin’s theory of evolution is drafted to explain politics and business, Dr. Wing argued for broad use of computer ideas. And not just for work. Applying computational thinking, “we can improve the efficiencies of our daily lives,” she said in an interview, “and make ourselves a little less stressed out.”


In his computer science course for nonmajors at the University of California, Berkeley, Dan Garcia wants students to understand why computers are “not magical.” In this exercise, students sort a deck of shuffled cards into ordered suits while being timed. They sort solo, then in pairs, then fours, then eights. But more people don’t always make it go faster. Amdahl’s law offers an equation to show that even with many computers tackling a problem, the time to complete the task does not decrease linearly. There are bottlenecks.CreditJim Wilson/The New York Times

Computing practices like reformulating tough problems into ones we know how to solve, seeing trade-offs between time and space, and pipelining (allowing the next action in line to begin before the first completes the sequence) have many applications, she said.

Consider the buffet line. “When you go to a lunch buffet, you see the forks and knives are the first station,” she said. “I find that very annoying. They should be last. You shouldn’t have to balance your plate while you have your fork and knife.” Dr. Wing, who equates a child filling her backpack to caching (how computers retrieve and store information needed later), sees the buffet’s inefficiency as a failure to apply logical thinking and sequencing.

Computational thinking, she said, can aid a basic task like planning a trip — breaking it into booking flights, hotels, car rental — or be used “for something as complicated as health care or policy decision-making.” Identifying subproblems and describing their relationship to the larger problem allows for targeted work. “Once you have well-defined interfaces,” she said, “you can ignore the complexity of the rest of the problem.”

Can computational thinking make us better at work and life? Dr. Krishnamurthi is sometimes seduced. “Before I go grocery shopping, I sort my list by aisles in the store,” he said. Sharing the list on the app Trello, his family can “bucket sort” items by aisle (pasta and oils, canned goods, then baking and spices), optimizing their path through Whole Foods. It limits backtracking and reduces spontaneous, “i.e., junk,” purchases, he said.

Despite his chosen field, Dr. Krishnamurthi worries about the current cultural tendency to view computer science knowledge as supreme, better than that gained in other fields. Right now, he said, “we are just overly intoxicated with computer science.”

It is certainly worth wondering if some applications of computational thinking are trivial, unnecessary or a Stepford Wife-like abdication of devilishly random judgment.

Alexander Torres, a senior majoring in English at Stanford, has noted how the campus’s proximity to Google has lured all but the rare student to computer science courses. He’s a holdout. But “I don’t see myself as having skills missing,” he said. In earning his degree he has practiced critical thinking, problem solving, analysis and making logical arguments. “When you are analyzing a Dickinson or Whitman or Melville, you have to unpack that language and synthesize it back.”

There is no reliable research showing that computing makes one more creative or more able to problem-solve. It won’t make you better at something unless that something is explicitly taught, said Mark Guzdial, a professor in the School of Interactive Computing at Georgia Tech who studies computing in education. “You can’t prove a negative,” he said, but in decades of research no one has found that skills automatically transfer.

Still, he added, for the same reasons people should understand biology, chemistry or physics, “it makes a lot of sense to understand computing in our lives.” Increasing numbers of people must program in their jobs, even if it’s just Microsoft Excel. “Solving problems with computers happens to all of us every day,” he said. How to make the skills available broadly is “an interesting challenge.”

“It’s like being a diplomat and learning Spanish; I feel like it’s essential,” said Greer Brigham, a Brown freshman who plans to major in political science. He’s taking the course designed by Dr. Krishnamurthi, which this term is being taught by a graduate student in robotics named Stephen Brawner.

On a March morning at the Brown computer science center, Mr. Brawner projected a student’s homework assignment on the screen. Did anyone notice a problem? Nary a humanities hand was raised. Finally, a young woman suggested “centimeters” and “kilograms” could be abbreviated. Fine, but not enough.

Mr. Brawner broke the silence and pointed out long lines of code reaching the far side of the screen. With a practiced flurry, he inserted backslashes and hit “return” repeatedly, which drew the symbols into a neat block. It may all be directions to a machine, but computer scientists care a great deal about visual elegance. As Mr. Brawner cut out repeated instructions, he shared that “whenever we define a constant, we want that at the top of our code.” He then explained the new assignment: write a program to play “rock, paper, scissors” against a computer.

Mili Mitra, a junior majoring in public policy and economics who sat with a MacBook on her lap, would not have considered this class a year ago. But seeing group research projects always being handed off to someone with computing knowledge, she decided that she “didn’t want to keep passing them along.” She has learned to write basic code and fetch data sets through the internet to analyze things she’s interested in, such as how geographic proximity shapes voting patterns in the United Nations General Assembly.

Despite finding interactions with a computer much like “explaining things to a toddler,” Ms. Mitra credits the class for instilling the habit of “going step by step and building a solution.” She admits to being an impatient learner: “I jump ahead. In C.S. you don’t have a choice. If you miss a step, you mess up everything.”

Just as children are drilled on the scientific method — turn observations into a hypothesis, design a control group, do an experiment to test your theory — the basics of working with computers is being cast as a teachable blueprint. One thing making this possible is that communicating with computers has become easier.

“Block” programming languages like Scratch, released by the M.I.T. Media Lab a decade ago, hide text strings that look like computer keys run amok. That makes coding look less scary. Instead of keyboard letters and symbols, you might select from a menu and drag a color-coded block that says “say ( ) for ( ) secs” or “play note ( ) for ( ) beats.” The colors and shapes correspond to categories like “sound” or “motion”; the blocks can be fit together like stacked puzzle pieces to order instructions. Students use this to, say, design a game.

One need not be a digital Dr. Doolittle, fluent in hard-core programming languages like Java or Python, to code. Block languages cut out the need to memorize commands, which vary depending on the computer language, because the block “is read just the way you think about it,” Dr. Garcia said. Students in his Berkeley course use the block language Snap! for assignments — he doesn’t teach Python until the last two weeks, and then just so they can take higher-level courses. “We tell them, ‘You already know how to program,’ ” he said, because the steps are the same.

Computer Science A, which teaches Java, is the fastest-growing Advanced Placement course. (The number of students taking the exam in 2016 rose 18 percent over 2015 and nearly tripled in a decade.) But professors complained that “Java was not the right way” to attract a diverse group of students, said Trevor Packer, head of the A.P. program, so a new course was developed.

The course, Computer Science Principles, is modeled on college versions for nonmajors. It lets teachers pick any coding language and has a gentler vibe. There is an exam, but students also submit projects “more similar to a studio art portfolio,” Mr. Packer said. The course covers working with data and understanding the internet and cyber security, and it teaches “transferable skills,” he said, like formulating precise questions. That’s a departure from what the College Board found in many high schools: “They were learning how to keyboard, how to use Microsoft applications.” The goal is that the new course will be offered in every high school in the country.

President Obama’s “Computer Science for All” initiative, officially launched last year, resulted in educators, lawmakers and computer science advocates spreading the gospel of coding. It also nudged more states to count computer science toward high school graduation requirements. Thirty-two states and the District of Columbia now do, up from 12 in 2013, according to It’s what Dr. Wing had hoped for when she advocated in her 2006 article that, along with reading, writing and arithmetic “we should add computational thinking to every child’s analytical ability.”


After arranging blocks into a sequence of commands, kindergartners at the Eliot-Pearson Children’s School scanned the bar codes on the blocks into their yellow robot. It obeyed their commands.CreditCharlie Mahoney for The New York Times

In an airy kindergarten classroom at Eliot-Pearson Children’s School, in the Tufts University Department of Child Study and Human Development, children program with actual blocks. Marina Umaschi Bers, a child development and computer science professor, created wooden blocks that bear bar codes with instructions such as “forward,” “spin” and “shake” that are used to program robots — small, wheeled carts with built-in scanners — by sequencing the blocks, then scanning them. Each “program” starts with a green “begin” block and finishes with a red “end.”

Coding for the youngest students has become the trendy pedagogy, with plentiful toys and apps like Dr. Bers’s blocks. Dr. Bers, who with M.I.T. collaborators developed the block language ScratchJr, is evangelical about coding. Learning the language of machines, she said, is as basic as writing is to being proficient in a foreign language. “You are able to write a love poem, you are able to write a birthday card, you are able to use language in many expressive ways,” she said. “You are not just reading; you are producing.”

Peer-reviewed studies by Dr. Bers show that after programming the robots, youngsters are better at sequencing picture stories. Anecdotally, she said, when they ask children to list steps for brushing teeth, they get just a few, “but after being exposed to this work, they’ll have 15 or 20 steps.”

Dr. Bers embeds computing in activities familiar to young children like inventing stories, doing dances and making art. At the Tufts school on a recent morning, children puzzled over a question: How does a robot celebrate spring?

“He’s going to dance, and then he will pretend that he is wet,” offered Hallel Cohen-Goldberg, a kindergartner with a mane of curls.

Solina Gonzalez, coloring a brown, blue and red circle with markers, peered soberly through pink-framed glasses: “He just does a lollipop dance.” Solina’s partner, Oisin Stephens, fretted about the root beer lollipop drawing she had taped to a block. “The robot won’t be able to read this,” he said. (It’s an invalid input.)

As they lurched around the carpet on their knees, the children executed computer science concepts like breaking instructions into sequenced commands, testing and debugging. One team used “repeat” and “stop repeat” blocks, forming a programming “loop,” a sequence of instructions that is continually repeated until a certain condition is reached.

Ideas For Teaching With Cardboard in Makerspaces

Cardboard Creators: Reusing to Learn

October 25, 2016
Switching from high school science to middle and high school gifted students has reawakened that sometimes uncomfortable sense of discovery of new teaching, where so much seems imperfect … I’m working with the mantra of imperfection.

That’s a good mantra for my students as well. Some students have never swung a hammer, threaded a needle, or made a model that was not outlined on card stock. Common day experiences have been digitized in our world, and access to extra materials is extremely limited for others. My solution: create a makerspace in my classroom and offer design challenges students can do with little more than string, glue, and cardboard. Cardboard, my makerspace material of choice, is available in every home in America.

From mac and cheese boxes to a shoebox, cardboard is a material that puts students on a level playing field. It’s free. Students can cut thin stuff with scissors or score corrugated material with a pair of safety scissors, and tape is cheap enough that I can send a partial roll home with a student who needs it. Kids in families who cannot afford clay or craft kits or have little money for additional classroom supplies can still imagine something using materials that belong to them. That equals the playing field among students who ‘have not’ with students who ‘have’ adequate resources.

Sure, many educators say, but this is learning time. How can cardboard be transformed into learning strategies benefiting students across disciplines? Here are four sample cardboard projects to get started.

1. Three-dimensional thinking by building artifacts. While it may seem unusual to us as educators, take the time to ask students how many have been in a barn, gone to a zoo, camped in a tent, or taken care of an animal. So many readings describe experiences for which students have no background knowledge. For example, Finding Winnie, the winner of the 2015 Caldecott Medal, is filled with unfamiliar venues. It took the illustrator, Sophie Blackall, over a year of research to visit all the places referenced in the book. My youngest middle school students are trying to build a single item model for just one scene in the book, ranging from an ocean liner to a tree to an antique car.

2. Imagining a Character. Middle school students love the idea of cosplay. Designing cardboard armor to imagine a warrior or superhero in a story is a simple way to use materials to portray their vision. The prompt can be as simple as, “Design a character to defend the castle.” It’s powerful to have the ability to create even an imperfect vision, instead of a project executed primarily by an overly helpful parent. Student processes are best remembered when the mistake or chance for failure becomes the driver for the learning.

3. Design thinking prototypes. The goal of design thinking is to solve a problem using a process of listening and developing empathy. Students struggle with this because they often design for themselves, rather than for a specific audience. After reading spooky stories that tie into both the Halloween season and the idea of justice, my students still struggled with the idea of putting themselves in another person’s shoes. How America is dealing with the idea of ‘liberty and justice for all’ is an example of a difficult idea. We used design thinking as the introduction to a conversation on empathy. Before the extended conversations at the end of the unit, I wanted to know if students could listen carefully. For one assignment, I asked them to set up a display prototype that combined scary elements from the stories and a building to contain a prisoner. While the artist of the classroom created a skeleton playing a trumpet by using scissors, this student didn’t follow directions, and his client (the teacher) was unsatisfied with the result. In contrast, the winner of the challenge created two ghosts out of cardboard shoulder pads and a turret out of thin cardboard, creating a powerful classroom lesson about utility versus perfection as well as listening.

4. Modeling. How does osmosis take place? What caused the creation of the universe? These are powerful questions, deep questions, and ones for which a teacher might not have the answer; however, they are just the type of questions my gifted students might ask. I pair students with an outside mentor via Skype or Google Hangouts by using the power of social media to find willing experts. To help students process difficult ideas, the Next Generation Science Standards recommend models as tools. Students often don’t think about making their own models unless teachers expose them to the idea as a strategy. Cardboard models are one way to go deeper in visible thinking and to augment visual notetaking. As described in Harvard’s Project Zero, initiatives like Agency by Design requires students to look closely at what they are doing to help discover complex ideas. When the students push back, I remind them of James Watson and Francis Crick, and how the cardboard models they created led to an understanding of DNA.

Tips on Creating a Cardboard Makerspace

  • Collect one or two plastic tubs of materials for your classroom.
    • In the first tub, start saving oddly-formed shapes of cardboard packaging from the IT department, or even toilet paper rolls. Corrugated cardboard is especially hard for younger students to cut. Resist the temptation to put full boxes in the box, or students will simply use them without modification (something I learned in this challenge).
    • In the second tub, place tape, string, and remnants of duct tape. I simply placed a box at my local church and asked for donations of half-used tape, white glue, and crochet thread.
  • Find donated materials. Reach out to close friends on Facebook, or check with a hardware store or custodian for unwanted materials.
  • Get a grant or donation from a big box store, or organize a campaign onDonorsChoose.
  • Build rubrics so students have a framework of expectations, but be willing to revise them as needed. The first creations may not be as rich as you expect, but this provides opportunities for further learning.

Building creations and making cardboard artists will also build memories in the journey of learning. Along the way, new skills and collaboration will help us become better learners.

How To Raise Brilliant Children, According To Science


The ideal student

LA Johnson/NPR

Becoming Brilliant

“Why are traffic lights red, yellow and green?”

When a child asks you a question like this, you have a few options. You can shut her down with a “Just because.” You can explain: “Red is for stop and green is for go.” Or, you can turn the question back to her and help her figure out the answer with plenty of encouragement.

No parent, teacher or caregiver has the time or patience to respond perfectly to all of the many, many, many opportunities like these that come along. But a new book, Becoming Brilliant: What Science Tells Us About Raising Successful Children, is designed to get us thinking about the magnitude of these moments.

Kathy Hirsh-Pasek, the book’s co-author, compares the challenge to climate change.

“What we do with little kids today will matter in 20 years,” she says. “If you don’t get it right, you will have an unlivable environment. That’s the crisis I see.”

Hirsh-Pasek, a professor at Temple University and a senior fellow at the Brookings Institution, is a distinguished developmental psychologist with decades of experience, as is her co-author, Roberta Golinkoff at the University of Delaware. And with this book, the two are putting forward a new framework, based on the science of learning and development, to help parents think about cultivating the skills people really need to succeed.

What follows is an excerpt from our conversation.

What led you to write this book now?

Golinkoff: We live in a crazy time, and parents are very worried about their children’s futures. They’re getting all kinds of messages about children having to score at the top level on some test. The irony is, kids could score at the top and still not succeed at finding great employment or becoming a great person.

Hirsh-Pasek: If Rip Van Winkle came back, there’s only one institution he would recognize: “Oh! That’s a school. Kids are still sitting in rows, still listening to the font of wisdom at the front of the classroom.”

We’re training kids to do what computers do, which is spit back facts. And computers are always going to be better than human beings at that. But what they’re not going to be better at is being social, navigating relationships, being citizens in a community. So we need to change the whole definition of what success in school, and out of school, means.

You present something you call the 21st-century report card. And it contains six C’s, which I’ve seen versions of elsewhere: collaboration, communication, content, critical thinking, creative innovation and confidence. But what’s new is the way you relate these skills to each other, and also, you’ve described what they look like at four levels of development.

Hirsh-Pasek: The first, basic, most core is collaboration. Collaboration is everything from getting along with others to controlling your impulses so you can get along and not kick someone else off the swing. It’s building a community and experiencing diversity and culture. Everything we do, in the classroom or at home, has to be built on that foundation.

Communication comes next, because you can’t communicate if you have no one to communicate with. This includes speaking, writing, reading and that all-but-lost art of listening.

Content is built on communication. You can’t learn anything if you haven’t learned how to understand language, or to read.

Critical thinking relies on content, because you can’t navigate masses of information if you have nothing to navigate to.

Creative innovation requires knowing something. You can’t just be a monkey throwing paint on a canvas. It’s the 10,000-hour rule: You need to know something well enough to make something new.

And finally, confidence: You have to have the confidence to take safe risks.

Golinkoff: There isn’t an entrepreneur or a scientific pioneer who hasn’t had failures. And if we don’t rear children who are comfortable taking risks, we won’t have successes.

OK, and for each of your six C’s, you also go into what they look like at four levels of development. Can you give us the deep dive on one of these?

Golinkoff: So, critical thinking. First you have to have content, right?

Most people at their desks at work have papers, books, magazines all over the place. Information is doubling every 2 1/2 years. We have to figure out how to select and synthesize the information we need.

So, at Level 1, we call it “seeing is believing.” If someone tells you alligators live in sewers in New York City, you buy it.

At Level 2, you see that truths differ; there are multiple points of view.

You learn Columbus discovered America, then you learn that there are alternative narratives — the Native Americans already lived here. This is kind of when critical thinking starts.

At the third level, we have opinions. All of us have used the phrase “they say.” That will get you into trouble because it shows little respect for science or evidence.

At Level 4, we talk about evidence, mastery, the intricacies of doubt.

E.O. Wilson, one of my heroes, the biologist, says we’re drowning in information and starved for wisdom. When we’re getting to be more at Level 4, we’ll see the gaps and the holes in a line of reasoning. Critical thinking is what leads to the next breakthroughs in any area.

In addition to breaking down the six C’s and four levels within each of them, you also cover the opportunities for parents, teachers and grandparents to cultivate those skills. Talk about that.

Golinkoff: So, if you’re going to have a kid who engages in critical thinking, you’re not going to shut them down when they ask a question. You’re not going to settle for “because.” You’re going to encourage them to ask more. And you want them to understand how other people think.

If you see a homeless person in the street: What do you think that person is thinking? How do you think they feel about not having a home?

Get someone else’s point of view activated to help them recognize that things are not always what they appear. That’s going to help them understand critical thinking.

OK, so that helps me understand how these skills are all interrelated. Perspective-taking, which I think of as a component of empathy, you’re saying is also foundational for critical thinking.

Hirsh-Pasek: Yes, theory of mind is important to be able to do critical thinking.

A big part of what you’re doing with this book is to try to get parents to supplement what’s going on in school. Talk a little more about that.

Hirsh-Pasek: One of the biggest concepts is breadth. Learning isn’t just K-12. It starts prenatally. If you get a bead on what your children are and aren’t being exposed to at school, that will suggest the kinds of experiences you want your children to have outside of school.

And you want people to look at where they themselves fall in the four levels within the 6 C’s, right? It’s not just for kids.

Hirsh-Pasek: Yes. I can say as a mom, well, let’s think about it — who am I as a collaborator? Am I an on-my-own kind of girl [Level 1] or a side-by-side [Level 2]?

When I was rushing my kids to get dressed and out the door, I was an on my own. I wish I weren’t!

It’s not a big deal to let my kid try to pick out his wardrobe. Who cares if it’s stripes and plaids? Let’s see that back-and-forth collaboration is built into our routines.

And then, how much communication is built in? Did we tell a joint story or did I just read the book and get it over with? It’s a really good idea to evaluate ourselves according to the grid. We can ask where we want to grow as parents.

Then we can ask, with the same grid: What do I want for my child? Where is my child now, and how can I build an environment in my house that will enable the child to grow up with these different skills?

Wow. OK. So this is really reinforcing the idea of learning as a social, relationship-oriented process. It’s not just a grid for sorting and measuring our kids; it’s about how we are relating to our kids.

Golinkoff: The other thing I think is crucial to notice is that we’re talking about doing things in the moment with your child. Notice we’re talking about buying nothing, signing up for no classes, and no tablets. Not that we’re Luddites, but we’re talking about how the crucible of social interaction between child and parent really helps set up the child for the development of these skills.

Corvallis students build, launch balloons

Corvallis Middle School seventh grade students spent three days of designing, cutting and gluing to create a hot-air balloon from tissue paper.


On Thursday morning, they tested the air-worthiness of their creations with a launch at the school’s football field and track.


Educator Stacy Jessop said the annual event is a 20-year tradition.

“We used to do an entire unit on aviation,” Jessop said. “Now there are so many other things to teach we just have a few days for this. We talk about structure, panels, design and the history of flight. We view the hot-air balloon show that happens each year in Albuquerque, New Mexico.”


Each balloon has a sign that says “If found return to Corvallis Middle School.”

“We have had a few fly away and we want to track how high and how far they go,” Jessop said. “We have had them go as far as Woodside, a mile or two.”


The 137 students were launching, chasing and repairing their balloons in groups of two and three. With the heat at 65 degrees and no breeze, most of the balloons did not fly farther than the field. The few that went further stuck in trees of homes in East Corvallis.

Teacher Dave Bradshaw said students were creative.


“Students make their own design,” Bradshaw said. “They glue the panels together and use a template to cut it out then they glue the pieces together. The balloons are very delicate. If there is any little hole the kids will find out when they put the hot air in there.”

Corvallis Middle School science teacher Chris Maul-Smith said he looks forward to the balloon project.


“It is a great way to celebrate the end of the year for students and for the teachers as well,” he said. “It is a way to bring everyone together and have fun constructing a balloon.”

Maul-Smith said the balloons rise up to 200 feet and travel usually 200 to 300 yards, depending on the weather. The colder the day the higher the balloons fly.

“We fill each balloon with hot air from a stove pipe that is attached to a heater donated from Mom’s Rentals in Hamilton,” he said. “They do this every year and make this possible. We hold the opening of each balloon over the stovepipe until it is super-filled and super-warm and then let it go. If there is enough temperature difference, they fly really well. Today is a much better temperature than yesterday.”


Maul-Smith and Dave Chimo filled the balloons and released them into the air.

The balloon team of Amanda Boelman and Madelyn Shepherd said it was a fun project.

“We learned about hot-air balloons and it was great,” Boelman said.


Stephanie Weber and Alexa Sunderland said creating and launching their balloon was cool.

“I was hoping it would go higher,” Weber said. “We’ve got the streamers on ours to make it extra fancy.”


Sunderland said, “It went farther than I thought but it would have been cool to go further and out of the field.”  Ramsey Snider and Carter Humphrey repaired their balloon’s several holes after their first launch.  This is Jennifer Powell’s first year to teach seventh grade. She was delighted to be included in this project that she has heard about for years.

  “Both my own children participated in this fun science project,” she said. “It is just the perfect day and the perfect ending to a great year of school.”

To Write Better Code, Read Virginia Woolf


Mountain View, Calif. — THE humanities are kaput. Sorry, liberal arts cap-and-gowners. You blew it. In a software-run world, what’s wanted are more engineers.

At least, so goes the argument in a rising number of states, which have embraced a funding model for higher education that uses tuition “bonuses” to favor hard-skilled degrees like computer science over the humanities. The trend is backed by countless think pieces. “Macbeth does not make my priority list,” wrote Vinod Khosla, a co-founder of Sun Microsystems and the author of a widely shared blog post titled “Is Majoring in Liberal Arts a Mistake for Students?” (Subtitle: “Critical Thinking and the Scientific Process First — Humanities Later”).

The technologist’s argument begins with a suspicion that the liberal arts are of dubious academic rigor, suited mostly to dreamers. From there it proceeds to a reminder: Software powers the world, ergo, the only rational education is one built on STEM. Finally, lest he be accused of making a pyre of the canon, the technologist grants that yes, after students have finished their engineering degrees and found jobs, they should pick up a book — history, poetry, whatever.

As a liberal-arts major who went on to a career in software, I can only scratch my head.

Fresh out of college in 1993, I signed on with a large technology consultancy. The firm’s idea was that by hiring a certain lunatic fringe of humanities majors, it might cut down on engineering groupthink. After a six-week programming boot camp, we were pitched headfirst into the deep end of software development.

My first project could hardly have been worse. We (mostly engineers, with a spritzing of humanities majors) were attached to an enormous cellular carrier. Our assignment was to rewrite its rating and billing system — a thing that rivaled maritime law in its complexity.

I was assigned to a team charged with one of the hairier programs in the system, which concerned the movement of individual mobile subscribers from one “parent” account plan to another. Each one of these moves caused an avalanche of plan activations and terminations, carry-overs or forfeitures of accumulated talk minutes, and umpteen other causal conditionals that would affect the subscriber’s bill.

This program, thousands of lines of code long and growing by the hour, was passed around our team like an exquisite corpse. The subscribers and their parent accounts were rendered on our screens as a series of S’s and A’s. After we stared at these figures for weeks, they began to infect our dreams. (One I still remember. I was a baby in a vast crib. Just overhead, turning slowly and radiating malice, was an enormous iron mobile whose arms strained under the weight of certain capital letters.)

Our first big break came from a music major. A pianist, I think, who joined our team several months into the project. Within a matter of weeks, she had hit upon a method to make the S’s hold on to the correct attributes even when their parent A was changed.

We had been paralyzed. The minute we tweaked one bit of logic, we realized we’d fouled up another. But our music major moved freely. Instead of freezing up over the logical permutations behind each A and S, she found that these symbols put her in the mind of musical notes. As notes, they could be made to work in concert. They could be orchestrated.

On a subsequent project, our problem was pointers. In programming language, a pointer is an object that refers to some master value stored elsewhere. This might sound straightforward, but pointers are like ghosts in the system. A single misdirected one can crash a program. Our pointer wizard was a philosophy major who had no trouble at all with the idea of a named “thing” being a transient stand-in for some other unseen Thing. For a Plato man, this was mother’s milk.

I’ve worked in software for years and, time and again, I’ve seen someone apply the arts to solve a problem of systems. The reason for this is simple. As a practice, software development is far more creative than algorithmic.

The developer stands before her source code editor in the same way the author confronts the blank page. There’s an idea for what is to be created, and the (daunting) knowledge that there are a billion possible ways to go about it. To proceed, each relies on one part training to three parts creative intuition. They may also share a healthy impatience for the ways things “have always been done” and a generative desire to break conventions. When the module is finished or the pages complete, their quality is judged against many of the same standards: elegance, concision, cohesion; the discovery of symmetries where none were seen to exist. Yes, even beauty.

To be sure, each craft also requires a command of the language and its rules of syntax. But these are only starting points. To say that more good developers will be produced by swapping the arts for engineering is like saying that to produce great writers, we should double down on sentence diagraming.

Here the technologists may cry foul, say I’m misrepresenting the argument, that they’re not calling to avoid the humanities altogether, but only to replace them in undergraduate study. “Let college be for science and engineering, with the humanities later.” In tech speak, this is an argument for the humanities as plug-in.

But if anything can be treated as a plug-in, it’s learning how to code. It took me 18 months to become proficient as a developer. This isn’t to pretend software development is easy — those were long months, and I never touched the heights of my truly gifted peers. But in my experience, programming lends itself to concentrated self-study in a way that, say, “To the Lighthouse” or “Notes Toward a Supreme Fiction” do not. To learn how to write code, you need a few good books. To enter the mind of an artist, you need a human guide.

For folks like Mr. Khosla, such an approach is dangerous: “If subjects like history and literature are focused on too early, it is easy for someone not to learn to think for themselves and not to question assumptions, conclusions, and expert philosophies.” (Where some of these kill-the-humanities pieces are concerned, the strongest case for the liberal arts is made just in trying to read them.)

How much better is the view of another Silicon Valley figure, who argued that “technology alone is not enough — it’s technology married with liberal arts, married with the humanities, that yields us the result that makes our heart sing.”

His name? Steve Jobs.



AUTHOR: RHETT ALLAIN, March 30, 2016

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