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 Lisa Durff

Here we are…there we are going « Connectivism - 0 views

  • Learning consists of weaving together coherent (personal) narratives of fragmented information. The narrative can be now created through social sensemaking systems (such as blogs and social networks), instead of centrally organized courses. Courses can be global, with many educators and participants (i.e. CCK08). Courses, unlike universities, are not directly integrated into the power system of a society. Can decentralized networks of autonomous agents serve the same function as organized institutions? But who loses, and what is lost, if the teaching role of universities decline?
    •  Lisa Durff
       
      So learning is developing a story from one's schema of a thing!
    •  Lisa Durff
       
      "But who loses, and what is lost, if the teaching role of universities decline?" My concern surrounds the word teaching. Who said that is their primary role? Isn't it licensing, formally sanctioning persons so they can enter the world of work with the "proper" credentials? Did you learn anything in your college days?
    •  Lisa Durff
       
      So what really needs to change is not the university, but the culture it serves...
  • The virtues that a society finds desirable are systematized in its institutions. However futile this activity, it helps society, and media, to hold people accountable, to devise strategies, and create laws so people feel safe. Similarly, results that are desirable (financial, educationally, etc) are systematized to ensure the ability to manage and duplicate results. I shared some thoughts on this systematization last year as a reason for the currently limited impact of personal learning environments (PLEs). Quite simply, even revolutionaries conserve.
  • Teaching is what is most at risk. Can a social network - loosely connected, driven by humanistic ideals - serve a similar role to what university classrooms serve today? I hope so, but I don’t think so. At least not with our current mindsets and skillsets. We associate with those who are similar. We do not pursue diversity. In fact, we shy away from it. We surround ourselves with people and ideas that resonate with our own, not with those that cause us stress or internal conflict. Secondly, until all of society becomes fully networked (not technologically networked, but networked on the principles of flows, connections, feedback), a networked entity always risks being subverted by hierarchy. Today, rightly or wrongly, hierarchy holds power in society.
    • Gina Minks
       
      What if the social network serves to exlude information from other groups? Who can fight against disenfranchisement if no one can see it any more because its filtered away?
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    Oh, George, so gloomy!
gobibijou

Stephen Downes - 0 views

  • ning 2.0 and the
    • gobibijou
       
      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
       
      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
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    downes talking about approaches in education. Web 2.0, elearning...
Lisa M Lane

The Public Domain: Enclosing the Commons of the Mind - 0 views

  •  
    In this enlightening book James Boyle describes what he calls the range wars of the information age-today's heated battles over intellectual property. Boyle argues that just as every informed citizen needs to know at least something about the environment or civil rights, every citizen should also understand intellectual property law. Why? Because intellectual property rights mark out the ground rules of the information society, and today's policies are unbalanced, unsupported by evidence, and often detrimental to cultural access, free speech, digital creativity, and scientific innovation.
Keith Hamon

Reflections on open courses « Connectivism - 4 views

  • In education, content can easily be produced (it’s important but has limited economic value). Lectures also have limited value (easy to record and to duplicate). Teaching – as done in most universities – can be duplicated. Learning, on the other hand, can’t be duplicated. Learning is personal, it has to occur one learner at a time. The support needed for learners to learn is a critical value point.
    • Ed Webb
       
      Excellent insight!
    • Keith Hamon
       
      Here's the key: if what we are typically doing in our classrooms can be easily duplicated, then it has lost its value in both the wider economy and in the educational ecosystem. We university professors must redefine the way we add value to our students' personal learning networks.
  • Learning, however, requires a human, social element: both peer-based and through interaction with subject area experts
  • Content is readily duplicated, reducing its value economically. It is still critical for learning – all fields have core elements that learners must master before they can advance (research in expertise supports this notion). - Teaching can be duplicated (lectures can be recorded, Elluminate or similar webconferencing system can bring people from around the world into a class). Assisting learners in the learning process, correcting misconceptions (see Private Universe), and providing social support and brokering introductions to other people and ideas in the discipline is critical. - Accreditation is a value statement – it is required when people don’t know each other. Content was the first area of focus in open education. Teaching (i.e. MOOCs) are the second. Accreditation will be next, but, before progress can be made, profile, identity, and peer-rating systems will need to improve dramatically. The underlying trust mechanism on which accreditation is based cannot yet be duplicated in open spaces (at least, it can’t be duplicated to such a degree that people who do not know each other will trust the mediating agent of open accreditation)
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  • The skills that are privileged and rewarded in a MOOC are similar to those that are needed to be effective in communicating with others and interacting with information online (specifically, social media and information sources like journals, databases, videos, lectures, etc.). Creative skills are the most critical. Facilitators and learners need something to “point to”. When a participant creates an insightful blog post, a video, a concept map, or other resource/artifact it generally gets attention.
  • Intentional diversity – not necessarily a digital skill, but the ability to self-evaluate ones network and ensure diversity of ideologies is critical when information is fragmented and is at risk of being sorted by single perspectives/ideologies.
  • The volume of information is very disorienting in a MOOC. For example, in CCK08, the initial flow of postings in Moodle, three weekly live sessions, Daily newsletter, and weekly readings and assignments proved to be overwhelming for many participants. Stephen and I somewhat intentionally structured the course for this disorienting experience. Deciding who to follow, which course concepts are important, and how to form sub-networks and sub-systems to assist in sensemaking are required to respond to information abundance. The process of coping and wayfinding (ontology) is as much a lesson in the learning process as mastering the content (epistemology). Learners often find it difficult to let go of the urge to master all content, read all the comments and blog posts.
  • e. Learning is a social trust-based process.
  • Patience, tolerance, suspension of judgment, and openness to other cultures and ideas are required to form social connections and negotiating misunderstandings.
  • An effective digital citizenry needs the skills to participate in important conversations. The growth of digital content and social networks raises the need citizens to have the technical and conceptual skills to express their ideas and engage with others in those spaces. MOOCs are a first generation testing grounds for knowledge growth in a distributed, global, digital world. Their role in developing a digital citizenry is still unclear, but democratic societies require a populace with the skills to participate in growing a society’s knowledge. As such, MOOCs, or similar open transparent learning experiences that foster the development of citizens confidence engage and create collaboratively, are important for the future of society.
Asako Yoshida

What is Connectivism trying to be? « Learning Games - 0 views

  • And while we can see that socio-linguistics is clearly emergent, without reference to specific phenomena that only exist at the social level the ability to understand and explain language change in society becomes quite constrained.
  • Minsky concludes that “it makes no sense to seek a single best way to represent knowledge”
 Lisa Durff

2¢ Worth » Personal Learning Networks - The Beginning - 2 views

  • the phrase, as we typically use it today, was most likely coined by George Siemens in his discriptions of connectivism,
  • The term ‘Personal Learning Network’ is directly derived from ‘Personal Learning Environment’, which as history shows was first used at the The Personal Learning Environments Session at a JISC/CETIS Conference in 2004.
  • http://www.elearnspace.org/Articles/learning_communities.htm – but it is the first time I believe I used the term “personal learning network” (2003)
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  • The most important inspiration for PLE was Illich’s four learning networks in Deschooling Society
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    Warlick's take on the PLN
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