Remove 2006 Remove Groups Remove Patterns Remove Wiki
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BMJ blogs " Blog Archive " Richard Smith: Get with Web 2.0 or become yesterday's person

Buzz Marketing for Technology

BMJ Group blogs. Search BMJ blog: You dont need to be signed in to read BMJ Group Blogs, but you can register here to receive updates about other BMJ Group products and services via our Group site. 10 Jun, 08 | by BMJ Group. RSS feeds, blogs, wikis, podcasts, social networking sites, mash up technology, etcâ??but

Web 2.0 188
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Personal Learning for Learning Professionals - Using Web 2.0 Tools to Make Reading & Research More Effective

Buzz Marketing for Technology

Monday, March 20, 2006. Group compound terms together - for example personalLearning is a tag I use. But it is a good idea to have a consist pattern to your tags to make life easier when you look things up. Preferrably, you would create a blog post or a wiki page with your analysis. Rapid eLearning Tools. eLearning Tools.

Web 2.0 122
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Six degrees of separation in instant messaging | Emerging Technology Trends | ZDNet.com

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The dataset which was collected in June 2006 contains summaries of 30 billion conversations among 240 million people. Of course, as you can see in the second map above, “there are obvious biases in the data, with 15- to 30-year-olds being by far the biggest groups of users. See the latest entries on the Intel wiki >>.

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eLearning & Deliberative Moments: The present and future of Personal Learning Environments (PLE)

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It was originally part of a class wiki. At the time of writing this introduction (August 2006), no particular product or service exists that can definitively be categorised as a PLE, although some prototypical work is in progress. In January 2006, Blackboard Inc. , Third-party modules may be added (eg KNotes weblog).

Web 2.0 165
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Communication (and Coordination?) in a Modern, Complex Organization

Buzz Marketing for Technology

Which groups are most likely to communicate with others in a large organization, regardless of social-and physical-boundaries? We analyze a dataset with millions of electronic mail messages, calendar meetings and teleconferences for many thousands of employees of a single, multidivisional firm during a three-month period in calendar 2006.