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Contents contributed and discussions participated by Ivan Travkin

Ivan Travkin

The Open Data Handbook - Open Data Manual - 4 views

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    This handbook discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to open up data. It discusses the why, what and how of open data - why to go open, what open is, and the how to 'open' data.
Ivan Travkin

Teaching in Social and Technological Networks « Connectivism - 6 views

  • Course content is similarly fragmented. The textbook is now augmented with YouTube videos, online articles, simulations, Second Life builds, virtual museums, Diigo content trails, StumpleUpon reflections, and so on.
  • Fragmentation of content and conversation is about to disrupt this well-ordered view of learning. Educators and universities are beginning to realize that they no longer have the control they once (thought they) did.
  • However, in order for education to work within the larger structure of integrated societal systems, clear outcomes are still needed.
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  • How can we achieve clear outcomes through distributed means? How can we achieve learning targets when the educator is no longer able to control the actions of learners?
  • Thoughts, ideas, or messages that the teacher amplifies will generally have a greater probability of being seen by course participants.
  • Each RT amplifies the message much like an electronic amplifier increases the amplitude of audio or video transmitters.
  • A curatorial teacher acknowledges the autonomy of learners, yet understands the frustration of exploring unknown territories without a map. A curator is an expert learner. Instead of dispensing knowledge, he creates spaces in which knowledge can be created, explored, and connected.
  • In CCK08/09, Stephen and I produced a daily newsletter where we highlighted discussions, concepts, and resources that we felt were important. As the course progressed, many students stated they found this to be a valuable resource -a centering point of sorts.
  • Today’s social web is no different – we find our way through active exploration. Designers can aid the wayfinding process through consistency of design and functionality across various tools, but ultimately, it is the responsibility of the individual to click/fail/recoup and continue.
  • Fortunately, the experience of wayfinding is now augmented by social systems. Social structures are filters. As a learner grows (and prunes) her personal networks, she also develops an effective means to filter abundance. The network becomes a cognitive agent in this instance – helping the learner to make sense of complex subject areas by relying not only on her own reading and resource exploration, but by permitting her social network to filter resources and draw attention to important topics. In order for these networks to work effectively, learners must be conscious of the need for diversity and should include nodes that offer critical or antagonistic perspectives on all topic areas. Sensemaking in complex environments is a social process.
  • After all, why should we do the heavy cognitive work when technology is uniquely suited to analyzing and generating patterns?
  • I’d like a learning system that functions along the lines of RescueTime – actively monitoring what I’m doing – but then offers suggestions of what I should (or could) be doing additionally. Or a system that is aware of my email exchanges over the last several years and can provide relevant information based on the development of my thinking and work. With the rise of social media, and with it the attention organizations pay to how their brand is being represented, monitoring services such as Viral Heat are promising. Imagine a course where the fragmented conversations and content are analyzed (monitored) through a similar service. Instead of creating a structure of the course in advance of the students starting (the current model), course structure emerges through numerous fragmented interactions. “Intelligence” is applied after the content and interactions start, not before. This is basically what Google did for the web – instead of fully defined and meta-described resources in a database, organized according to subject areas (i.e. Yahoo at the time), intelligence was applied at the point of search. Aggregation should do the same – reveal the content and conversation structure of the course as it unfolds, rather than defining it in advance.
  • Filtering resources is an important educator role, but as noted already, effective filtering can be done through a combination of wayfinding, social sensemaking, and aggregation. But expertise still matters. Educators often have years or decades of experience in a field. As such, they are familiar with many of the concepts, pitfalls, confusions, and distractions that learners are likely to encounter. As should be evident by now, the educator is an important agent in networked learning. Instead of being the sole or dominant filter of information, he now shares this task with other methods and individuals.
  • By determining what doesn’t belong, a learner develops and focuses his understanding of a topic. The teacher assists in the process by providing one stream of filtered information. The student is then faced with making nuanced selections based on the multiple information streams he encounters. The singular filter of the teacher has morphed into numerous information streams, each filtered according to different perspectives and world views.
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