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If you share the work of others, it’s your duty to make sure that the creators of that work get proper credit. Crediting work in our copy-and-paste age of reblogs and retweets can seem like a futile effort, but it’s worth it, and it’s the right thing to do. You should always share the work of others as if it were your own, treating it with respect and care. When we make the case for crediting our sources, most of us concentrate on the plight of the original creator of the work. But that’s only half of the story—if you fail to properly attribute work that you share, you not only rob the person who made it, you rob all the people you’ve shared it with. Without attribution, they have no way to dig deeper into the work or find more of it.

The problem, of course, is that those students represent the precise group MOOCs are meant to serve. “MOOCs were supposed to be the device that would bring higher education to the masses,” Jonathan Rees noted. “However, the masses at San Jose State don’t appear to be ready for the commodified, impersonal higher education that MOOCs offer.” Thrun’s cavalier disregard for the SJSU students reveals his true vision of the target audience for MOOCs: students from the posh suburbs, with 10 tablets apiece and no challenges whatsoever—that is, the exact people who already have access to expensive higher education. It is more than galling that Thrun blames students for the failure of a medium that was invented to serve them, instead of blaming the medium that, in the storied history of the “correspondence” course (“TV/VCR repair”!), has never worked. For him, MOOCs don’t fail to educate the less privileged because the massive online model is itself a poor tool. No, apparently students fail MOOCs because those students have the gall to be poor, so let’s give up on them and move on to the corporate world, where we don’t have to be accountable to the hoi polloi anymore, or even have to look at them, because gross.

SG_Debug && SG_Debug.pagedebug && window.console && console.log && console.log('[' + (new Date()-SG_Debug.initialTime)/1000 + ']' + ' Bottom of header.jsp'); SlateEducationGetting schooled.Nov. 19 2013 11:43 AM The King of MOOCs Abdicates the Throne 7.3k 1.2k 101 Sebastian Thrun and Udacity’s “pivot” toward corporate training. By Rebecca Schuman &nbsp; Sebastian Thrun speaks during the Digital Life Design conference on Jan. 23, 2012, in Munich. Photo by Johannes Simon/Getty Images requirejs(["jquery"], function($) { if ($(window).width() < 640) { $(".slate_image figure").width("100%"); } }); Sebastian Thrun, godfather of the massive open online course, has quietly spread a plastic tarp on the floor, nudged his most famous educational invention into the center, and is about to pull the trigger. Thrun—former Stanford superprofessor, Silicon Valley demigod, and now CEO of online-course purveyor Udacity—just admitted to Fast Company’s openly smitten Max Chafkin that his company’s courses are often a “lousy product.” Rebecca Schuman Rebecca Schuman is an education columnist for Slate. Follow This is quite a “pivot” from the Sebastian Thrun, who less than two years ago crowed to Wired that the unstemmable tide of free online education would leave a mere 10 purveyors of higher learning in its wake, one of which would be Udacity. However, on the heels of the embarrassing failure of a loudly hyped partnership with San Jose State University, the “lousiness” of the product seems to have become apparent. The failures of massive online education come as no shock to those of us who actually educate students by being in the same room wit

nd why the answer is not the MOOC, but the tiny, for-credit, in-person seminar that has neither a sexy acronym nor a potential for huge corporate partnerships.

What is a learner profile? &nbsp;A learner profile includes three elements: Learning transcript: grades, courses (and/or learning levels), state and district achievement data Personalized learning information: supplemental achievement data, record of services received, feedback on work habits, record of extracurricular activities and work/service experiences. Portfolio of student work: collection of personal best work products.

What about children with disconnected parents? As the number of learning options expands many students and families would benefit from a chosen guide. The Donnell Kay Foundation imagines a new system of education where learners create customized paths with advocates who work with them to connect their present learning to their desired future. This role of mentor/advocate/coach could benefit all students but particularly students without the benefit of engaged parents. In some cases, parents/guardians will choose to allow designees (e.g., mentors, relatives) to manage learner profile privacy settings. Young people in the foster care and juvenile justice system may have a court (or state) appointed guide that would manage privacy settings.

Data Quality Campaign recently noted, “With access to current education data child welfare staff can help the highly mobile students in foster care achieve school success by providing support such as the following: helping with timely enrollment and transfer of credits if a school change is needed, identifying the need for educational supports, working with school staff to address attendance and discipline issues, and assisting with transition planning to post-school activities such as higher education.”

Increasingly, they judge our character.

Upstart has over the last 15 months lent $135 million to people with mostly negligible credit ratings. Typically, they are recent graduates without mortgages, car payments or credit card settlements.

ZestFinance, is a former Google executive whose company writes loans to subprime borrowers through nonstandard data signals.

The self-confident founders of Kreditech lend money through the Internet: short-term mini-loans of up to €500, with the average customer receiving €109. Instead of requiring credit information from their customers, they determine the probability of default on their own, using a social scoring method that consists of high-speed data analysis. "Ideally, the money should be in customers' accounts within 15 minutes of approval.

Kreditech also requires access to Facebook profiles, so that it can verify whether a user's photo and location match information on other social networking sites, like Xing and LinkedIn -- and whether his or her friends include many with similar education levels or many colleagues working in the same company.

All of this increases the likelihood that Kreditech is dealing with a real person.

A strong workforce is vital to our nation's economic prosperity, and it has become more critical than ever that our workforce acquire advanced skills and postsecondary credentials. By 2020, 65 percent of jobs will require a college degree or postsecondary credential.

prior learning assessment (PLA), which enables non-traditional learners to complete training and degree programs sooner by awarding them college credit based on the college-level knowledge, skills and abilities they've gained outside of the classroom.

Many state policy leaders have begun to recognize the importance and potential of PLA and have been developing statewide strategies.

Algorithms have become one of the most powerful arbiters in our lives. They make decisions about the news we read, the jobs we get, the people we meet, the schools we attend and the ads we see. Yet there is growing evidence that algorithms and other types of software can discriminate.

The people who write them incorporate their biases, and algorithms often learn from human behavior, so they reflect the biases we hold.

Fairness, Accountability and Transparency in Machine Learning workshop, which considers the role that machines play in consequential decisions in areas like employment, health care and policing.

The expression "Big Brother" has become dated. Experts would seem to have reached consensus on the term "Big Data" to describe the new favorite topic of discussion in boardrooms, at conventions like Berlin's re:publica last week, and in a number of new books. Big Data promises both total control and the logical management of our future in all aspects of life.

New is the way companies, government agencies and scientists are now beginning to interpret and analyze their data resources. Because storage space costs almost nothing nowadays, computers, which are getting faster and faster, can link and correlate a wide variety of data around the clock. Algorithms are what create order from this chaos. They dig through, discovering previously unknown patterns and promptly revealing new relationships, insights and business models. Though the term Big Data means very little to most people, the power of algorithms is already everywhere. Credit card companies can quickly recognize unusual usage patterns, and hence automatically warn cardholders when large sums are suddenly being charged to their cards in places where they have never been. Energy companies use weather

According to official figures, since the Swedish capital Stockholm began using algorithms to manage traffic, drive times through the city's downtown area have been cut in half and emissions reduced by 10 percent. Online merchants have recently started using the analyses to optimize their selling strategies. The widespread phrase "Customers who bought this item also bought …" is only one example of the approach.

Encouraged by Watson Sr. and his executive team, employees often formed their own study groups. One, known as the Owl Club, allowed employees to study any subject they wanted at company expense. Such programs evolved into adult learning classes, and eventually into grants for employees to pursue college credits and degrees

Today, industry specialists around the world in IBM Global Business Services use an array of e-learning tools—including podcasts and Twitter—customer on-site classes, and IBM conferences and classrooms to educate customers on everything from the use of social media and cloud computing, to how to build a smarter rail system. And IBM employees worldwide take advantage of their networked community to draw upon each other’s skills day and night to solve customer problems and develop the capabilities clients value most.

40% to 45% of what we do every day sort of feels like a decision, but it’s actually habit.

There’s a cue, which is like a trigger for the behavior to start unfolding, A routine, which is the habit itself, the behavior, the automatic sort of doing what you do when you do a habit.

And then at the end, there’s a reward. And the reward is how our neurology learns to encode this pattern for the future.