Skip to main content

Home/ CCK0809/ Group items tagged brain

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
Ed Webb

The Transducer » Blog Archive » Brain Behavior and Behaving like Brains - 2 views

transducer.ontoligent.com/...599

transducer cognition education learning

shared by Ed Webb on 15 Oct 09 - Cached
  • boundaries are inserted where the brain experiences what Zacks calls “prediction error” — when things break a pattern of repetition and thus signal to the brain a boundary that is used to construct the temporal model for the event — its typical sequence. 
  • the response of the audience — comprised mainly of educational experts — and of Zacks himself is that one practical lesson from his research is that creators of narrative content, such as film, should make an effort to provide more obvious segmentation in their products.  Clearly, if this is how the brain works, we should work this way too. I think this is a major fallacy that pervades the reception of brain science research.  People tend to assume that if the brain works a certain way, then so should we.
  • the lesson is to get good at perceiving and creating event boundaries, which requires not pre-segmented media, but the opposite — hard to grasp art, stuff that violates expectations and rewards the perciever with a different perspective.   In fact, giving students media with well defined boundaries may cause their capacity to construct boundaries to atrophy, much as caffeine causes our adrenal glands to shrink. (I know, it’s a good reason to stop drinking coffee.)
  • ...1 more annotation...
  • So, what is the pedagogical and media design lesson here?  Learning Teaching is not about making content easy to ingest, it’s about creating environments where students can play this game of meaning formation, which isn’t always stress-free.  Marketers may disagree, but they are in the business of indoctrination, not teaching.
Ed Webb

Neuro-tweets: #hashtagging the brain - Research - University of Cambridge - 4 views

www.cam.ac.uk/...o-tweets-hashtagging-the-brain

neuroscience twitter networks connectivism connectiveknowledge

shared by Ed Webb on 20 Jun 11 - No Cached
  • human brain networks represent a balance between high efficiency of information transfer and low connection cost
  • Members of the audience and other Twitter users were asked to tweet during the lecture about the concepts that were being discussed, using the hashtag #csftwitterbrain. At the end of the talk Professor Bullmore displayed the resulting image showing the interconnectivity of the hashtagged tweets, and explained how Twitter networks can be compared to the human brain network. “We found that the #twitterbrain network was somewhat like the brain network in being small-world and modular with highly connected hub nodes; however the brain network was more clustered and less efficient than the twitter network. So at first sight there were some points in common and some points of difference between these two information processing networks.”
  • “It has been intriguing to see the spectacle of watching the twitter network grow or evolve over the course of several days. And I have learnt a lot about the power of new media to engage and communicate, and the potential scientific value of using Twitter to map and measure social networks.”
gobibijou

Stephen Downes - 0 views

www.blip.tv/840097

downes elearning education web2.0

shared by gobibijou on 24 Sep 09 - Cached
  • ning 2.0 and the
    • gobibijou
      gobibijou on 24 Sep 09
       
      S. Downes: http://www.blip.tv/file/840097 2 approaches to learning - tradiotional (AI): old artifitial technology. Expert system organises. Old managnement systems. Focus on: - Goal orientated. - Competencies. - Efficency (from A to B in the most efficient). Requieres: - an expert - knowledge representation (VS. Siemens: the knowledge that we have CAN'T be represented) for expl. language -- Problem: it creates a simplification of the knowledge. - learning activities are set up by an expert. -network approach: (???IDF). Conectivism (born 40 years ago Pappert &?). Computational system is NOT set up as a representational system BUT is set up as a NETWORK (like a brain). The connectivist system: - is unnorganized - is unstructured (previously) - looks messy and unorganised - can NOT be predicted HOw Knowledge is represented in the system? DISTRIBUTED. Our concept of X is not a symbolic representation but a set up of active connections also in a neuronal level (?) Model of learning NOt based in deduction and inference BUT on ASSOCIATION based on: - concurrency. - proximity. - back propagation (economics: supply and demand market is based on that) - ???Amealing the way form networks/community in society work in THE SAME WAY that they do in a neuronal level and a personal level. Communities ARE networks that work through distributed connections. How should be the network? - DIVERSITY (wide representation of different points of views) Knowledge in a network is: EMERGENT - AUTONOMY : each individual is self-directed. Each individual works as his own guide. - CONNECTEDNESS (or interactivities). Knowledge produced by mechanism of interaction is produced by the nature/properties of the network. The way/organization of connections are formed is essential. - OPENESS (there's no inside/outside the "system"). Connection FLOWS freely. RECOGNITION of patterns (clustter). LEARNERS: Learners have different things they want to learn and the system
  • 2.0 and the impact of web 2
    • gobibijou
      gobibijou on 24 Sep 09
       
      S. Downes: http://www.blip.tv/file/840097 NOtes (need to be double checked) 2 approaches to learning 1. traditional (AI): old artifitial technology. Expert system organises. Old managnement systems. Focus on: - Goal orientated. - Competencies. - Efficency (from A to B in the most efficient). Requieres: - an expert - knowledge representation (VS. Siemens: the knowledge that we have CAN'T be represented) for expl. language -- Problem: it creates a simplification of the knowledge. - learning activities are set up by an expert. 2.-network approach: (???IDF). Conectivism (born 40 years ago Pappert &?). Computational system is NOT set up as a representational system BUT is set up as a NETWORK (like a brain). The connectivist system: - is unnorganized - is unstructured (previously) - looks messy and unorganised - can NOT be predicted HOw Knowledge is represented in the system? DISTRIBUTED. Our concept of X is not a symbolic representation but a set up of active connections also in a neuronal level (?) Model of learning NOt based in deduction and inference BUT on ASSOCIATION based on: - concurrency. - proximity. - back propagation (economics: supply and demand market is based on that) - ???Amealing the way form networks/community in society work in THE SAME WAY that they do in a neuronal level and a personal level. Communities ARE networks that work through distributed connections. How should be the network? - DIVERSITY (wide representation of different points of views) Knowledge in a network is: EMERGENT - AUTONOMY : each individual is self-directed. Each individual works as his own guide. - CONNECTEDNESS (or interactivities). Knowledge produced by mechanism of interaction is produced by the nature/properties of the network. The way/organization of connections are formed is essential. - OPENESS (there's no inside/outside the "system"). Connection FLOWS freely. RECOGNITION of patterns (clustter). LEARNERS: Learners have different thin
  • gobibijou on 24 Sep 09
     
    downes talking about approaches in education. Web 2.0, elearning...
Ed Webb

The 'Web Squared' Era - Forbes.com - 0 views

www.forbes.com/...-breakthroughs-web2point0.html

TimOReilly web web2.0 future ARG augmented ubiquity RFIDs

shared by Ed Webb on 25 Sep 09 - No Cached
  • Web 2.0, the name we gave this phenomenon in 2004 when we named our new conference, turns five on Oct. 5
  • Web Squared.
  • Web Squared is another way of saying "Web meets World."
  • ...3 more annotations...
  • collective intelligence applications are increasingly driven by cascades of sensor data being thrown off by devices, often without explicit human intervention. Today’s smartphones contain microphones and cameras, as well as motion, proximity, location, and direction sensors. They have their own eyes, ears, and sense of touch. Revolutionary new applications connect those senses to cloud databases and programs running on massive server farms.
  • Where the Web Squared world gets really interesting, though, is when applications use all the senses of a device, coordinating them much like the human brain coordinates our senses, to draw conclusions that would be difficult with one sense alone.
  • our world will have "information shadows." Augmented reality amounts to information shadows made visible.
Ed Webb

It's Time To Hide The Noise - 5 views

www.techcrunch.com/...its-time-to-hide-the-noise

noise signal twitter filtering apps tweetdeck seesmic twhirl techcrunch opinion

shared by Ed Webb on 04 Oct 09 - Cached
  • the noise is worse than ever. Indeed, it is being magnified every day as more people pile onto Twitter and Facebook and new apps yet to crest like Google Wave. The data stream is growing stronger, but so too is the danger of drowning in all that information.
  • the fact that Seesmic or TweetDeck or any of these apps can display 1,200 Tweets at once is not a feature, it’s a bug
  • if you think Twitter is noisy, wait until you see Google Wave, which doesn’t hide anything at all.  Imagine that Twhirl image below with a million dialog boxes on your screen, except you see as other people type in their messages and add new files and images to the conversation, all at once as it is happening.  It’s enough to make your brain explode.
  • ...2 more annotations...
  • all I need is two columns: the most recent Tweets from everyone I follow (the standard) and the the most interesting tweets I need to pay attention to.  Recent and Interesting.  This second column is the tricky one.  It needs to be automatically generated and personalized to my interests at that moment.
    • Lisa Durff
      Lisa Durff on 04 Oct 09
       
      How do you determine which are the most interesting tweets? What is your criteria?
    • Ed Webb
      Ed Webb on 04 Oct 09
       
      Aye, there's the rub. This is where those clever algorithms come in that monitor your activity and make suggestions. Like Amazon recommendations. Er, which are always brilliantly spot-on. Or something.
  • search is broken on Twitter.  Unless you know the exact word you are looking for, Tweets with related terms won’t show up.  And there is no way to sort searches by relevance, it is just sorted by chronology.
  • Ed Webb on 04 Oct 09
     
    Signal/noise ratio is an issue in networks
1 - 8 of 8
Showing 20▼ items per page