Ever since we first introduced the term "Web 2.0," people have been asking, "What’s next?" Assuming that Web 2.0 was meant to be a kind of software version number (rather than a statement about the second coming of the Web after the dotcom bust), we’re constantly asked about "Web 3.0." Is it the semantic web? The sentient web? Is it the social web? The mobile web? Is it some form of virtual reality?
It is all of those, and more.
The Web is no longer a collection of static pages of HTML that describe something in the world. Increasingly, the Web is the world – everything and everyone in the world casts an "information shadow," an aura of data which, when captured and processed intelligently, offers extraordinary opportunity and mind bending implications. Web Squared is our way of exploring this phenomenon and giving it a n
Sarah Allen has been the only woman on a team of computer programmers a few times in the more than two decades she has worked in the field. Most notably, she led the team — as the lone female programmer — that created Flash video, the dominant technology for streaming video on the Web.
Since only about 20 percent of all programmers are women, her experience isn't uncommon, and now she's trying to bring more women into the field.
Allen says the number of women who major in computer science has actually been going down. She hopes that making women in the field more visible to each other will help young women see that there is a path for them in what is one of the fastest growing professions in the world.
What if you could switch the two? What if you could teach concepts of programming languages upfront – even to kids? This seemingly simple switch has many advantages. Learners have a fast on-ramp and interest. They learn at a unique pace and keep up interest. They see how programming applies to real life problems at a very early stage of their learning and they learn complex concepts of programming within a wider context
Thus, our end goal is not to teach programming. Rather, it is to enable the participants to rapidly master any programming language and in doing so, explore computer science.
One of the side-effects of the explosion of startups all around the world is that several colleagues have already expressed some interest towards various courses that claim to teach someone "the basics of programming", whatever the hell that may be, for a nice round sum like £500 or £800 or thereabouts, in a single day.
I know I won't raise any eyebrows in the actual tech scene with this article. Anyone who's learned how to program knows that there's no magic wand that will miraculously teach you how to program in a day, not for £500 or for any amount of money. You can't teach someone to program in a day any more than you can teach someone to ski or write or ride horses in a day. Those things take time.
In my view, there is one factor that anyone who wants to learn how to program well must have: a sense of fascination at the idea that you can tell computers what to do.
We now understand that literacy is a right that belongs to every human being.
There is absolutely no reason why you can't join Avi Fombaum, David Byttow, Ellen Ullman (who has a degree in English), and John Pavley on the road to coding. The skill of coding is no different from the skill of reading and writing English or any human language. Forthousands of years literacy belonged to the rich, the powerful, and their administrators. We now understand that literacy is a right that belongs to every human being. In the same way, we live in a coding illiterate world where the skill of programming computers belongs to a priesthood. The Flatiron School, Hacker School, General Assembly, and Codecademy are here to break that priesthood and let us in.
In the About page for this blog, I wrote, “Computing Education Research is about how people come to understanding computing, and how we can facilitate that understanding.” Juha Sorva’s dissertation (now available!) helped me come to an understanding of what it means to “understand computing.” I describe a fairly technical (in terms of cognitive and learning sciences) definition, which basically is Juha’s. I end with some concrete pedagogical recommendations that are implied by this definition.
So here’s the full definition: Computing education research is about understanding how people develop robust models of notional machines, and how we can help them achieve those mental models.
Just about everyone has a personal stake in language, and many people — expert and amateur — feel entitled to an opinion. But linguists care more than most people, and when linguistics hit the media, linguists can get very agitated indeed.
Published earlier this month in the Proceedings of the National Academy of Sciences (PNAS), the latest paper to upset linguists around the world uses methods from computational evolutionary science to look at questions about language prehistory.
Using computer programs to analyze creative writing is a branch of digital humanities – a field so new that it's still considered controversial in certain circles. "In the academy, I think it's viewed with a mixture of excitement and apprehension," Professor Ted Underwood said. However, Underwood's father is in computer science, and Underwood spent summers during his undergraduate years working for his dad, writing computer programs. Combining that skill with his passion for literature comes naturally to the English professor, but he realizes it may not come so easily to his colleagues.
"What I'm trying to do now is create tools that will make it easier for other researchers to use this bigger collection," he said.
Susan Einhorn's insight:
Computer science and computational thinking offering new insights in the humanities. Computational thinking is impacting and helping us learn more about every field of knowledge.
That might seem obvious to some, but it's worth dwelling on in an education context. Coding is just a fundamental tool, the same way writing in English and algebra are. Moreover, having a basic understanding of how technology actually functions and is developed is becoming important across more and more industries. Yet most schools don't treat it that way. They look at it as a niche. Later on in the day, during a Q&A with Minnesota Senator Amy Klobouchar, an audience member expressed frustration with the fact that not every state treats computer programming as a course that can fulfill core math requirements the way, say, algebra does. Perhaps it's time to change that. Or, at more ambitious schools, maybe it's time to think of ways to work coding into other subjects, the way students exercise their writing skills in social studies, or with science papers.
Brookville Elementary students engaging in a programming lab at Miami. Computational thinking is not the study of computer science, but rather a paradigm that is increasingly becoming more necessary as the traditional liberal arts begin to encounter problems of scale. The concepts of computational thinking include fundamental concepts of computer science including identifying and restating the problem in order to understand the domain and context, analyzing alternative solutions to determine the best way to attack a problem (often using abstraction, decomposition, and tradeoff analysis to make seemingly intractable problems tractable), working in multidisciplinary teams to solve large problems that no one person can solve alone, and putting all of the gained knowledge together in order to produce a solution.
EdSurge (blog) Learn To Code, Code To Learn EdSurge (blog) The act of writing also engages people in new ways of thinking. As people write, they learn to organize, refine, and reflect on their ideas. In the process of learning to code, people learn many other things. They are not just learning to code, they are coding to learn.
See more from the AT&T Archives at http://techchannel.att.com/archives NOTE: film is silent. A corollary to A Computer Technique for the Production of Animated Movies, the film illustrates the first part of the process, what the program looked like and how the program would be fed into the computer and rendered. From 1964.
Currently much of the big data being churned out is merely exhaust. But imagine the possibilities once we figure out how to produce and process better data on the fly on a global scale. Call it Big Inference.
I'm thinking Gaia's brain: distributed but unified intelligences that gather data from sensors all over the world, and that synthesize those data streams to perceive the overall state of the planet as naturally as we perceive with our own sensory systems.
We need to gather the data. We need the processing power to interpret the data. We need the algorithms. To actually make sense of the data and decide what actions and responses to take, we have to figure out how to extract high-level patterns and concepts from the raw inputs. There is an ongoing debate over the right approach.
Computational thinking involves conceptualizing, not just coding and learning the syntax of a language, and it's more about the ideas, not the artefacts. It is the thinking we employ to design solutions, not the end product or ...
Where technology hasn’t penetrated in a meaningful way is in professional development. Teachers are still “improving” their skills in more or less the same way they were decades ago. This has to change. If you’re teaching in a STEM-related area and you cannot or will not understand variable assignment, iteration, recursion, and other basic concepts — the very basics of coding — you should find a new career. I’m not saying you need to delve into pointers, concurrency, etc. Just the basics.
Regional accents are a major part of what makes American English so interesting as a dialect.
Joshua Katz, a Ph. D student in statistics at North Carolina State University, just published a group of awesome visualizations of Professor Bert Vaux and Scott Golder's linguistic survey that looked at how Americans pronounce words. (via detsl on /r/Linguistics)
Susan Einhorn's insight:
Very interesting use of technology to explore linguistics.
....while children comfortably learn the WHAT (blocks or syntax) of programming languages and environments, the HOW and WHY is much harder as they construct programming solutions.
If the goal is to develop robust thinking skills while kids are being creative, collaborative, participatory and all that other good stuff, the focus of the learning needs to go beyond the tool, the syntax of a programming language and even the work products to the deeper thinking skills. While the fun features afforded by these programming environments make for great engagement, they often draw away focus to the artifacts, many of which employ relatively thin use of computational thinking.
The inadvertent peril posed by the “learn to code” mania and the cornucopia of websites advocated by avenues such as Code.org is that they may (unwisely) be equated to “CS education” for K-12 schools and educators lacking capacity and skills for teaching computing. While not so drastic, it is somewhat akin to confusing architecture with construction.
It also perpetuates the misconception that CS equals programming and that children should code for the sake of coding rather than giving due attention to other important reasons for why schools should want kids to program--to promote a way of thinking and problem solving, to use computing in intelligent ways in their future careers, and yes, possibly get excited about computer science as a discipline, and be primed for success should they choose to pursue CS.
Mr. Arkiletian said he prefers to teach students by being a strong role model and providing a challenging environment.
“What I’m kind of providing them is a model of the passion and the enthusiasm and the doggedness, the persistence that you have to have to get those high heights, one step at a time.
During his 14 years of teaching computer programming at Eric Hamber, many of Mr. Arkiletian’s students have gone on to study computer science in university.
Computer science gives you an easy way of helping people around the world,” he said. “If you create something today, it can benefit people tomorrow.”
“One thing that was great about his class is he very much encouraged us to go beyond what he was teaching in the class. He encouraged us to start our own projects that were not necessarily directed by him and let us follow our own passions."
SEATTLE — One of the great frustrations for advocates of computer science education is that programming classes are treated as electives in most high schools across the country, rather than as a core part of students’ education.
Students like Sam Blazes and Wilfried Hounyo, two winners in the 2012 National STEM Video Game Challenge, say they see their passion for computer programming is potentially leading them into a wide range of future professions.
“There’s no specific place you can plan on going because there are so many different things you can do with programming,” Blazes told an audience during a panel discussion at The Atlanticmagazine’s Technologies in Education Forum earlier this month. “You can do pretty much anything with it that you can program.”
Forty years ago, when large mainframe computers roamed the earth, few experts gave much thought to how these mammoth machines could be used for education, and fewer still about how they could help young learners create, explore, and learn through technology. At the time, highly trained programmers still worked in inaccessible languages that mainly processed numbers. But all that changed with a turtle. In 1967, MIT professor Seymour Papert and colleagues developed Logo, an early language for children. Its main innovation? A small robot--the turtle--that students could easily program to move or rotate. For the first time, young programmers got instant feedback and a physical manifestation of their commands.
"I don't think any high school classes could prepare someone fully for a hackathon," says Jennie. "I've been lucky that my dad has been able to teach me a lot, but I also learn a lot through friends, and sites likeStackOverflow. The three computer classes have given a solid foundation as a programmer, but I find myself learning a completely new concept -- like a new language -- every hackathon. I think between the three hackathons I've attended this year, and the year-long AP Computer Science class, I've learned exponentially more at hackathons."
Cordis News An expedition into the programmable city Cordis News Indeed, some analysts predict that we are entering a new phase of 'everyware', where computational power will be distributed and available at any point on the planet for people to use...
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