MOOCthink
Responding to Linda Harasim's comment, here:
To Mohsen Saadatmand: there is indeed significant overlap between communities of interest and cMOOCs and the underlying mechanisms are the same. The difference between the communities and the MOOCs is that the former are persistent while the latter are occasional. Thus, the two play different roles: the communities embed knowledge and standardize practice, while the MOOCs disrupt existing patterns of thinking and introduce people to new connections and new ideas.
To Linda Harasim: interesting and engaging comment. I do not think that artificial intelligence will be in any particular way better than human intelligence. But I think that anything that is a network – and this includes networks of machines as well as networks of humans or networks of neurons – can develop intelligence. There is substantial evidence to suggest that this is true, and I think it is no longer sufficient to suggest that the theory is simply an instance of “magical thinking.”
Take one particular point you make, for example. You write: “Siemens and Downes expected that somehow 2,000 participants should self-manage their learning by forming interest groups: how would or could 2000 strangers meet and self-organize into functioning learning groups? How would each individual know how to identify their interests?” The suggestion that this is impossible, that strangers could not self-organize, is refuted by reams of evidence. From tag-based communities to clusters on interest groups on Google Groups to the threads in Metafilter and 4chan, people have shown a remarkable ability to self-organize. And the research on our MOOCs (and even some xMOOCs) shows that this happens in MOOCs as well, and that these self-organizations have a learning focus.
But I also think you misunderstand the role of technology in cMOOCs. You write, “the ultimate organizer and decision-maker in the learning network (whether formal or non-formal) is that artificial intelligence (neural networks) replace the teacher or the moderator or the organizer. Technology replaces the human who is making the decisions and organizing the interactions.” This is simply not true, and nothing I have developed or advocated leans this way.
Technology makes learning networks possible; technology creates the channels through which people can interact, but it is people – each one of them making their own decisions – who choose what to read, what to link to, what to create, what to say. The ultimate organizers and decision makers in the learning network are students.
Can machines learn? Sure they can, of course they can, anything that is networked can learn. Simple stupid neurons, when joined together, can learn. So can simple stupid computers. But the most interesting results happen when you take networks of humans and, instead of telling them what to do, enable them to make decisions for themselves. Now you have networks of learning networks. You get remarkable results, like memes, cat photos, and maybe, global democracy. And it’s not magic. It’s the simple, observable, science of networks.
To Mohsen Saadatmand: there is indeed significant overlap between communities of interest and cMOOCs and the underlying mechanisms are the same. The difference between the communities and the MOOCs is that the former are persistent while the latter are occasional. Thus, the two play different roles: the communities embed knowledge and standardize practice, while the MOOCs disrupt existing patterns of thinking and introduce people to new connections and new ideas.
To Linda Harasim: interesting and engaging comment. I do not think that artificial intelligence will be in any particular way better than human intelligence. But I think that anything that is a network – and this includes networks of machines as well as networks of humans or networks of neurons – can develop intelligence. There is substantial evidence to suggest that this is true, and I think it is no longer sufficient to suggest that the theory is simply an instance of “magical thinking.”
Take one particular point you make, for example. You write: “Siemens and Downes expected that somehow 2,000 participants should self-manage their learning by forming interest groups: how would or could 2000 strangers meet and self-organize into functioning learning groups? How would each individual know how to identify their interests?” The suggestion that this is impossible, that strangers could not self-organize, is refuted by reams of evidence. From tag-based communities to clusters on interest groups on Google Groups to the threads in Metafilter and 4chan, people have shown a remarkable ability to self-organize. And the research on our MOOCs (and even some xMOOCs) shows that this happens in MOOCs as well, and that these self-organizations have a learning focus.
But I also think you misunderstand the role of technology in cMOOCs. You write, “the ultimate organizer and decision-maker in the learning network (whether formal or non-formal) is that artificial intelligence (neural networks) replace the teacher or the moderator or the organizer. Technology replaces the human who is making the decisions and organizing the interactions.” This is simply not true, and nothing I have developed or advocated leans this way.
Technology makes learning networks possible; technology creates the channels through which people can interact, but it is people – each one of them making their own decisions – who choose what to read, what to link to, what to create, what to say. The ultimate organizers and decision makers in the learning network are students.
Can machines learn? Sure they can, of course they can, anything that is networked can learn. Simple stupid neurons, when joined together, can learn. So can simple stupid computers. But the most interesting results happen when you take networks of humans and, instead of telling them what to do, enable them to make decisions for themselves. Now you have networks of learning networks. You get remarkable results, like memes, cat photos, and maybe, global democracy. And it’s not magic. It’s the simple, observable, science of networks.
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