Collective Intelligence & Distance Learning
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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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Forget notecards, Cerego wants to help you memorize with new online learning tool

Forget notecards, Cerego wants to help you memorize with new online learning tool | Collective Intelligence & Distance Learning | Scoop.it
Cerego, a company that has operated out of Tokyo since 2000, has opened an office stateside and is launching a new memory management tool based on principles drawn from cognitive science.

Whether you’re studying up on U.S. History, wine tasting terminology or how to fly a Cessna, Cerego believes its new online tool is the most effective way to remember what you learn.

While several new startups and learning platforms provide formal students and lifelong learners the opportunity to take courses on all kinds of subjects, Andrew Smith Lewis, Cerego’s cofounder and executive chairman, says his product applies learning principles drawn from neuroscience and cognitive science.

As students progress through courses on the site, Cerego takes a “spaced rehearsal” approach, which supports a learning technique that involves the repetition of content over increasing periods of time, to calculate the optimal moments to review content. The algorithms consider what students got right and wrong, as well as their familiarity with related content and, potentially, what others on the platform found challenging or easy to determine how likely they are to forget specific content items and when that content should be reviewed.

“They’re like interactive notecards that are smart and know exactly what you know and don’t know,” said Lewis. The site has been seeded with about 50 courses on topics from exotic animals to statistics to American cuts of beef, but the goal is for users – whether they’re students, professors, casual learners, publishers or even corporations – to add to the site with their own content. College students could use it to study for a test on anatomy or adult learners – including those taking courses on online learning sites like Coursera and Udacity – could use it to review programming terminology, Lewis said.

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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 | Scoop.it
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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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 | Scoop.it
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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Now Building Hubbl, A “Gamified” App Discovery Platform

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

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 | Scoop.it
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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