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Collective Intelligence & Distance Learning
Collective intelligence is a shared or group intelligence involving knowledge creation and flow. Pooled brainpower emerges from the collaboration and learning actions of a community of connected individuals empowered by social media, participatory tools, and mobile platforms.
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Five Ways Social Media Has Forever Changed the Way We Work

Five Ways Social Media Has Forever Changed the Way We Work | Collective Intelligence & Distance Learning |

Collective intelligence

Organizations have the ability to leverage the experience and wisdom of an entire workforce to solve a problem or identify an opportunity instead of just relying on a specific team. After speaking at a conference recently someone from a large oil and gas company told me how they couldn't solve a problem of a drill melting at extremely hot temperatures. They posed the problem on their collaborative platform for the thousands of other employees to try to solve and received a solution which was worth over a billion dollars.



Being able to come across a person or piece of information that can be used to improve a situation is a valuable thing. Organizations who deploy collaborative solutions greatly improve the chances of this happening. Employees have the ability to discover information which they can contribute to in a positive way. Lowe's Home Improvement saw this first hand when an employee asked for more of a product to be delivered to a store which other stores were not selling much of. Eventually this employee shared a demo she was doing at one of her stores to sell out of the product and other locations quickly followed. This employee who was asking for additional product happened to share her demo which resulted in over a million dollars in additional revenue.


Easy to find people and information

Email and static intranets are the default forms of communication and collaboration within many organizations. This leads to around 25-30 percent of an employees work week spent in front of email and a large amount of duplicated content. Enterprise collaboration platforms have enabled a much more effective way to find people and information. A way which is self-sufficient (meaning you don't need to ask anyone for anything) and empowering to the employees.


Anyone can be a leader and employees have a voice

When most employees think of a leader at their company they typically think of an executive. Social media has changed what it means to be a leader. Employees now have a voice where they can share their ideas for anyone within the company to see and read. These employees have the ability to become leaders in their own right on any topic that they care about. One of the world's largest consulting firms in the world (hundreds of thousands of employees around the world) has seen this happen first hand where junior and mid-level employees have the most widely followed internal blogs in the company. These employees are not executives but they are leaders with a voice that everyone listens to.


Transparency and flatness

Most organizations in the world are hierarchical and not transparent. It's analogous to climbing a ladder where only the first few rungs are visible and the rest are hidden. This is changing and many organizations are no longer using this as the way to work. Employees (including managers and executives) are now sharing what they are working on, how they are feeling, who they are meeting with, and what is happening with their department or the company as a whole in a discoverable and public way. There is greater insight for employees to understand not just what is happening in their organization but how their individual contributions are impacting something greater. 

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Bing Adds Social Sidebar Mod

Bing Adds Social Sidebar Mod | Collective Intelligence & Distance Learning |
Yesterday Microsoft’s Bing released an all new design for their social sidebar, a version less cluttered and better linked to friends and trends.

Designed to present Bing users with relevant results of friend networks via Foursquare, Twitter, Facebook, and Klout, the social side of search is still located on the right side of a user’s desktop, but with more minimalist style and ease of use too.

Besides a cleaner and edgy look, Bing users no longer have to hover over people to catch on to added and deeper content. A little + icon lets users drill down to get more info, which is a nice touch. The Official Bing Blog tells more of these improvements, and while not exactly what anyone would call “sweeping innovation”, the incremental change is nice. Regardless of what anyone thinks of Bing, the practicality of social sharing and suggestion come through with some of these refinements
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Now Building Hubbl, A “Gamified” App Discovery Platform

Now Building Hubbl, A “Gamified” App Discovery Platform | Collective Intelligence & Distance Learning |

Here’s how it works.


Hubbl captures the opinions about an app from around the web by aggregating content from mainstream media articles, blogs and app enthusiasts. It combines these opinions with those from your friends on Facebook (if you sign up with Facebook), your friends on Hubbl and the Hubbl community at large in order to organize the apps into smart collections. These collections aren’t just general categories like “games” or “social,” but can be narrowly focused on one particular app feature, too. For example, Evernote is a Productivity and Note-taking tool, but you can tag it “LifeLogging” if that’s what you use it for. 


These categories work like Twitter hashtags in the app. If you tap on “LifeLogging” in the above example, you would come across a list of apps that also fit that genre. And then you may end up tapping on one of those apps’ other hashtags to follow drill down into a different feature set, too. There’s a feeling of serendipitous, zigzagging discovery here.


In Hubbl, you can explore apps by popular tags, you can view those trending in the news, or you can view the stream of the apps your friends recommend within different sections of the platform (“Explore,” “Buzz,” “Stream”). However, the game element comes into play under “Contests.” Every day, Hubbl will have a contest where users submit or vote on the most appropriate tag for a given app. The first person to submit the winning tag gets a $15 iTunes Gift Card. The idea here is to create an incentive to classify the newly added apps – not the Evernotes and Instagrams, necessarily, but those that aren’t yet tagged.


Hubbl says that the contests are needed because people get tired of curation after some point, and it’s difficult to maintain a network around app organization and friends’ recommendations when people stop participating. With contests, users are encouraged to return the app and to help Hubbl continue to classify the new additions. The contests would also be open to sponsorship, too, allowing app publishers to take over the contest for the day and offer their own award for help in picking out the best tags for their app, as well.


It’s an interesting concept to use a gamification element to encourage repeat visits to an app discovery platform, and people certainly like to win stuff, so it could catch on. However, Hubbl isn’t quite ready yet for its big debut – that’s still a few weeks out - so it’ s hard to review the experience based on what we can test right now. Final judgement is on hold.

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Video discovery app Vodio lands on the iPhone, launches Highlights feature

Video discovery app Vodio lands on the iPhone, launches Highlights feature | Collective Intelligence & Distance Learning |
Video discovery platform Vodio has updated its iOS app to make it available on iPhones, the Israeli startup Vodio Labs announced today. In addition, the new version is also an upgrade ...


Vodio has been described as a ‘Flipboard for videos.’ Thanks to its free app, users can browse videos from different sources in one place. According to the startup, its users have watched a quarter of a million hours of video and generated over two million video plays since its launch.


Users can follow pre-built thematic channels, they can also connect Vodio with their social networks, and the app will aggregate videos shared by their friends for easy browsing. Yet, it is worth noting that sharing is optional, and turned off by default.


While the new app shares many characteristics with the previous iPad version, it also includes new features such as ‘Highlights’, which the company describes as Vodio’s equivalent of Flipboard’s Cover Stories. In practical terms, this new channel helps users find relevant content across all their channels, feeds and interests, by pulling all the videos that Vodio’s algorithm predicts they will enjoy.

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AppHero Raises $1.8 Million For App Recommendation Service Which Learns Your Interests From Facebook

AppHero Raises $1.8 Million For App Recommendation Service Which Learns Your Interests From Facebook | Collective Intelligence & Distance Learning |
Following Apple's acquisition of Chomp, the app search and discovery business continues to heat up.


App Hero is building an app recommendation service that helps users find new applications to try by analyzing their historical activity and their social data. It also includes a friending functionality so users can see which apps their friends are installing and recommending.


At first glance, this setup sounds very similar to what the mobile app recommendation platform Crosswalk is currently doing. Like AppHero, Crosswalk keeps track of your apps and allows you to recommend your favorite ones to others. And it does a better job at figuring out your interests than iTunes Genius does, in my opinion.


However, while Crosswalk taps into Facebook (and other services) to discover which of your friends are on the platform, AppHero takes a different route – it actually uses your Facebook data to help it make its recommendations.


A recent high school graduate, Satok started AppHero in May 2011, finding inspiration in the untapped potential of mobile technology. “These devices are capable of so much, and people are under-utilizing them,” he says. “I’ve been thinking about how we can deliver the most value to consumers, and it led down this path of thinking about the space of personalization.”


He thinks that AppHero is a better tool for app discovery than an app search site because search is only great when you already know what you’re looking for. “But people don’t know what they don’t know,” he says. As for the comparisons with Crosswalk and the like, he claims the big differentiator is the underlying intelligence in AppHero. Not only does the service understand “who someone is and what they’re like,” Satok says, it also learns more about them over time by tracking their Facebook social data (think: updated location, marital status, likes etc.) and activity (e.g., geo-location, app downloads and likes/dislikes).

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Mozilla Launches Open Badges 1.0, A New Standard to Recognize and Verify Online Learning and Education

Mozilla Launches Open Badges 1.0, A New Standard to Recognize and Verify Online Learning and Education | Collective Intelligence & Distance Learning |

As web-based learning platforms proliferate, and education increasingly happens in formal and informal settings and in both real and virtual classrooms, there is a growing need for a new form of credentialing that reflects these changes. Traditional, paper-based diplomas and certificates are no longer enough, but designing a meaningful, universal replacement for the old standard doesn’t happen over night. Luckily, Mozilla is on the case.


The Open Badges framework is designed to allow any learner to collect badges from multiple sites, tied to a single identity, and then share them out across various sites, including personal blogs to social networking channels. It is critical for this infrastructure to be open to give learners control over their own learning and credentials, allow anyone to issue badges, and for each learner to carry their badges with them across the Web and other contexts.


Its goals further elucidate Mozilla’s mission, which is simply to provide a system “for alternative accreditation, credentialing, and recognition” and help those alternative credentials “expand beyond siloed environments to be broadly shareable” and to “truly support learners learning everywhere.


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Huffington Post Now Has Its Own “Labs” Site For Online News Experiments

Huffington Post Now Has Its Own “Labs” Site For Online News Experiments | Collective Intelligence & Distance Learning |

News publishers are becoming tech companies, right down to the Google Labs style experimental sites: The New York Times Company Research & Development Lab, The Globe Lab, WapPo Labs...


And now there’s HuffPost Labs, which will unveil its first project today: Highlights, a collection of the most popular sentences from articles and blog posts across the Huffington Post empire.Labs co-founder Conor White Sullivan explains that there are two ways a reader can “vote” for a sentence: either by selecting the text and clicking the new “Highlight” button that will start appearing on Huffing Post today, or by simply copying the selection.


The sentences are also judged by the ratio of highlights to page views, since articles and blog posts that are featured on the front page of Huffington Post or get more traffic than posts that are deeper in the site’s navigation. So a sentence that received lots of highlights even though it got a relatively small number of page views will be treated as very interesting on the Highlights page. This should help surface interesting stories that might otherwise be overlooked.


Lead designer Andrew Sass, said the concept came out of the team’s desire to solve the information overload problem. “It’s sort of ironic working on this at HuffPost, but no person can read as much content as we’re publishing,” Sullivan says.


They hit on the idea of highlighting sentences because what people choose to copy, whether that’s into an e-mail or into some storage system like Evernote, is much more personal than choosing to share a URL. Also, Sullivan happened to really like finding news through e-mail lists, where people tend to copy snippets of articles to share with other subscribers.



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YogiPlay Debuts “YogiMeter,” An Educator-Based Rating System For Children’s Learning Apps

YogiPlay Debuts “YogiMeter,” An Educator-Based Rating System For Children’s Learning Apps | Collective Intelligence & Distance Learning |
YogiPlay, a Menlo Park-based company from husband-and-wife team Cedric and Michal Selling, is attempting to tackle the critical problem of surfacing appropriate, trusted, and carefully vetted educational apps for children.


“It’s using the same principles I’ve been using all along from my knowledge of child development and interactive media,” he says of YogiMeter. “I’ve structured in a way with some very specific ways to look at how and why kids would be engaged, and if they’re engaged, how and why they might learn.” He also vetted this rubric with other colleagues not associated with YogiPlay to get their feedback and input.


While there are a few startups working to rank and review mobile apps, like KinderTown, for instance (which also vets apps with educators), Dr. Gray says that he believes the YogiMeter system uses a more developmental approach with techniques common to those familiar in child development and education. “The others are not as rigorous, research-based, structured and consistent,” he says describing YogiMeter’s competition.


The system he developed ranks and analyzes apps in two main areas - engagement and educational quality. For determining an app’s engagement, it looks at things like user interactions, user experience, intrinsically motivated engagement, extrinsically motivated engagement and socially motivated engagement.


And to analyze the app’s ability to teach, it looks at whether the app will actually engage the child in learning, as it proposes to do, and whether that learning is deep, authentic, personalized, differentiated, and whether or not parents can track the child’s progress throughout.



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Facebook Launches Recommendations Bar For Suggesting Articles

Facebook Launches Recommendations Bar For Suggesting Articles | Collective Intelligence & Distance Learning |
Ten Months after Facebook announced the recommendations bar at f8, it's finally getting its official release to help sites suggest content to you based on what friends are reading.


When you’re reading an article on a site that has implemented the Recommendations Bar, a small pop up will appear at the bottom, showing you recommended articles based on your friends’ activity.

Similar to the current Like button, if you like an article using the Recommendations Bar, the story is published on your timeline and appears in your friends’ news feed.

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Tipflare: Two MIT Seniors Build A One-Stop Shop For Recommendations On Anything | TechCrunch

Tipflare: Two MIT Seniors Build A One-Stop Shop For Recommendations On Anything  |  TechCrunch | Collective Intelligence & Distance Learning |
With so much information, content and so many services now living online, there's a lot of choice -- even for something as simple as where to go to buy a new pair of socks. Oh, and there's a lot of...


With so much information, content and so many services now living online, there’s a lot of choice — even for something as simple as where to go to buy a new pair of socks. Oh, and there’s a lot of data. As it’s evolved and gotten better at making sense of its new Big Data, the Web has become an extraordinary engine for discovering new stuff: News, cat videos, porn, you name it. Naturally, scores of sites are becoming (or are building) recommendation engines to help users wade through the noise, and, dining on Big Data, they get smarter every day.


However, as it stands today, the discovery process is pretty fragmented, as recommendation engines tend to be domain-specific. Want to find a good movie? Try Netflix. Want to find a good book? Go to GoodReads, etc. And this fragmentation makes for a crappy user experience.


So, frustrated with the fact that there’s no one-stop shop for great recommendations on, well, everything, a couple of seniors at MIT have developed, and quietly launched, Tipflare to be that general solution. While the site’s creators, Hayden Metsky and Thiago Vieira, have bigger ambitions, today Tipflare focuses in on giving users one place to find quality recommendations on books, movies, songs, and restaurants — in a jiffy.


If you’ve ever struggled to find a recommendation for a good book that’s actually based on what you like to read and not just your browsing or purchase history (Amazon, for example) and then repeat that for a good movie, Tipflare’s value is obvious. If not, you might just say, hey, why not go to GoodReads or Amazon or Netflix? And it’s true that, using Netflix as an example, those that specialize in one domain will probably be better at recommending (say, movies) than a generalist.

But the Tipflare creators aren’t worried about that. If you want to watch something on Netflix, you’ll discover on Netflix. Instead, Tipflare really aims to differentiate itself from other services by being broad in focus while trying to keep the design and UX as clutter-free and as easy to use as possible.


Users simply enter what movies or books they like — or import their “likes” from Facebook, and the site instantly serves recommendations on what they’ll go bananas for based on what they already enjoy, factoring in Facebook friends’ interests, your location (for restaurants, specifically), the day of the week, time of day, etc. so that it can offer “New for You” recommendations when you come back.


Like Triposo, the travel and destination recommendation service we recently covered, Tipflare leans heavily on its algorithms to serve quality recommendations. But it also incorporates social cues as well, though Metsky says that Tipflare’s social integration is really a tool to back up and support its algorithm. It’s the supporting cast, not the star.


While Tipflare has a lot to recommend it (see what I did there?), it’s not a panacea. In other words, it’s not yet that next-gen, hyper-intelligent personal assistant; it still requires work on the part of the user. One day in the not-so-distant future, the Web, search, etc. will transition from a demand-based system (where you input what you want and a service tells you where to go), to one that’s more actively directive in telling you what to do and where to go based on your history, behavior, browsing, and more.


The site is early in its gestation and still has a long way to go, but the founders are asking the right questions. When it comes to algorithmic recommendations and discovery, there’s a trust issue. Google and so many others are addressing this with friendsourced and social graph-authenticated recommendations and results. The core reason for this being, hey, you’re probably going to trust recommendations from real people, especially those who know you and your tastes, more than a machine — even if those algorithms are wizardry.

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