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it is a simplistic and short- sighted phrase that suggests if every student had a device and if every teacher were trained to use these devices, then student learning would rise automatically.

Adding a digital device to the classroom without a fundamental change in the culture of teaching and learning will not lead to significant improvement.

Let’s drop the phrase “one-to-one” and refer instead to “one-to- world.”

The planning considerations now evolve from questions about technical capacity to a vision of limitless opportunities for learning.

As soon as you shift from “one- to-one” to “one-to-world,” it changes the focus of staff development from technical training to understanding how to design assignments that are more empowering—and engage students in a learning community with 24-hour support

Perhaps the weakest area of the typical one-to-one computing plan is the complete absence of leadership development for the administrative team

Craft a clear vision of connecting all students to the world’s learning resources.

Model the actions and behaviors they wish to see in their schools.

Support the design of an ongoing and embedded staff development program that focuses on pedagogy as much as technology.

Move in to the role of systems analyst to ensure that digital literacy is aligned with standards.

Ensure that technology is seen not as another initiative, but as integral to curriculum.

support risk- taking teachers

creating cohorts of teachers across disciplines and grades who are working on innovative concepts

Mathtrain.TV.

how much responsibility of learning can we shift to our students

How can we build capacity for all of our teachers to share best practices with colleagues in their school and around the world?

How can we engage parents in new ways?

How can we give students authentic work from around the world to prepare each of them to expand their personal boundaries of what they can accomplish?

publishing their work to a global audience.

That’s not to say there isn’t any room for humans in Demand’s process. They just aren’t worth very much. First, a crowdsourced team of freelance “title proofers” turn the algorithm’s often awkward or nonsensical phrases into something people will understand: “How to make a church-pew breakfast nook,” for example, becomes “How to make a breakfast nook out of a church pew.” Approved headlines get fed into a password-protected section of Demand’s Web site called Demand Studios, where any Demand freelancer can see what jobs are available. It’s the online equivalent of day laborers waiting in front of Home Depot. Writers can typically select 10 articles at a time; videographers can hoard 40. Nearly every freelancer scrambles to load their assignment queue with titles they can produce quickly and with the least amount of effort — because pay for individual stories is so lousy, only a high-speed, high-volume approach will work. The average writer earns $15 per article for pieces that top out at a few hundred words, and the average filmmaker about $20 per clip, paid weekly via PayPal. Demand also offers revenue sharing on some articles, though it can take months to reach even $15 in such payments. Other freelancers sign up for the chance to copyedit ($2.50 an article), fact-check ($1 an article), approve the quality of a film (25 to 50 cents a video), transcribe ($1 to $2 per video), or offer up their expertise to be quoted or filmed (free). Title proofers get 8 cents a headline. Coming soon: photographers and photo editors. So far, the company has paid out more than $17 million to Demand Studios workers; if the enterprise reaches Rosenblatt’s goal of producing 1 million pieces of content a month, the payouts could easily hit $200 million a year, less than a third of what The New York Times shells out in wages and benefits to produce its roughly 5,000 articles a month.

But once it was automated, every algorithm-generated piece of content produced 4.9 times the revenue of the human-created ideas. So Rosenblatt got rid of the editors. Suddenly, profit on each piece was 20 to 25 times what it had been. It turned out that gut instinct and experience were less effective at predicting what readers and viewers wanted — and worse for the company — than a formula.

Here is the thing that Rosenblatt has since discovered: Online content is not worth very much. This may be a truism, but Rosenblatt has the hard, mathematical proof. It’s right there in black and white, in the Demand Media database — the lifetime value of every story, algorithmically derived, and very, very small. Most media companies are trying hard to increase those numbers, to boost the value of their online content until it matches the amount of money it costs to produce. But Rosenblatt thinks they have it exactly backward. Instead of trying to raise the market value of online content to match the cost of producing it — perhaps an impossible proposition — the secret is to cut costs until they match the market value.

a burst at the start and top-ups through company training—is breaking down. One reason is the need for new, and constantly updated, skills.

The 19th and 20th centuries saw stunning advances in education. That should be the scale of the ambition today

It is easier to learn later in life if you enjoyed the classroom first time around: about 80% of the learners on Coursera already have degrees. Online learning requires some IT literacy, yet one in four adults in the OECD has no or limited experience of computers. Skills atrophy unless they are used, but many low-end jobs give workers little chance to practise them.

WHEN education fails to keep pace with technology, the result is inequality.

in the basic forms, as well as in the content of people's thinking.

The early 1930

had experienced the conditions necessary to alter radically the content and form of their thought.

we expected that they would display a predominance of those forms of thought that come from activity that is guided by the physical features of familiar objects.

Therefore we began, as most field work with people does, by emphasizing contact with the people who would serve as our subjects. We tried to establish friendly relations so that experimental sessions seemed natural and non-threatening. We were particularly careful not to conduct hasty or unprepared presentations of the test materials.

As a rule, our experimental sessions began with long conversations which were sometimes repeated with the subjects in the relaxed atmosphere of a tea house, where the villagers spent most of their free time, or in camps in the field and in mountain pastures around the evening campfire. These talks were frequently held in groups. Even when the interviews were held with one person, the experimenter and other subjects made up a group of two or three who listened attentively to the person being interviewed and who sometimes offered remarks or comments on what he said. The talk often took the form of a free-flowing exchange of opinion between participants, and a particular problem might be solved simultaneously by two or three subjects, each proposing an answer. Only gradually did the experimenters introduce the prepared tasks, which resembled the “riddles” familiar to the population and therefore seemed like a natural extension of the conversation.

He characterized primitive thinking as “prelogical” and “loosely organized.” Primitive people were said to be indifferent to logical contradiction and dominated by the idea that mystical forces control natural phenomena

We conceived the idea of carrying out the first far-reaching study of intellectual functions among adults from a non-technological non-literate, traditional society

hamlets

nomad

1. Women living in remote villages who were illiterate and who were not involved in any modern social activities. There were still a considerable number of such women at the time our study was made. Their interviews were conducted by women, since they alone had the right to enter the women's quarters. 2. Peasants living in remote villages who were in no way involved with socialized labor and who continued to maintain an individualistic economy. These peasants were not literate. 3. Women who attended short-term courses in the teaching of kindergarteners. As a rule, they had no formal schooling and almost no training in literacy. 4. Active kolhoz (collective farm) workers and young people who had taken short courses. They were involved as chairmen running collective farms, as holders of other offices on the, collective farm, or as brigade leaders. They had considerable experience in planning production, distributing labor, and taking stock of output. By dealing with other collective farm members, they had acquired a much broader outlook than isolated peasants. But they had attended school only briefly, and many were still barely literate. 5. Women students admitted to teachers school after two or three years of study. Their educational qualifications, however, were still fairly low.

Short-term psychological experiments would have been highly problematic under the field conditions we expected to encounter