Social Media is Killing the LMS Star - A Bootleg of Bryan Alexander's Lost Presentation... - 0 views
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Note that this isn’t just a technological alternate history. It also describes a different set of social and cultural practices.
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CMSes lumber along like radio, still playing into the air as they continue to gradually shift ever farther away on the margins. In comparison, Web 2.0 is like movies and tv combined, plus printed books and magazines. That’s where the sheer scale, creative ferment, and wife-ranging influence reside. This is the necessary background for discussing how to integrate learning and the digital world.
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These virtual classes are like musical practice rooms, small chambers where one may try out the instrument in silent isolation. It is not connectivism but disconnectivism.
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Guest Post: The Complexities of Certainty | Just Visiting - 0 views
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Privileges abound in academia, but so do experiences of loss, instability and fear. And into this situation we were called to respond to a pandemic.
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It is tempting to reach for certainties when everything around us is in chaos, and for a vast swath of higher ed instructors, the rapid shift from face-to-face teaching to emergency distance learning has been chaos. Small wonder, then, that people have offered -- and clung to -- advice that seeks to bring order to disorder. Many people have advised instructors to prioritize professionalism, ditching the sweatpants and putting away the visible clutter in our homes before making a Zoom call, upholding concepts like "rigor" so that our standards do not slip. To some, these appeals to universal principles are right-minded and heartening, a bulwark against confusion and disarray. But to others they have felt oppressive, even dangerously out of touch with the world in which we and our students live.
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certainties can be dangerous; their very power is based upon reifying well-worn inequities dressed up as tradition
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I unintentionally created a biased AI algorithm 25 years ago - tech companies are still... - 0 views
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How and why do well-educated, well-intentioned scientists produce biased AI systems? Sociological theories of privilege provide one useful lens.
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Scientists also face a nasty subconscious dilemma when incorporating diversity into machine learning models: Diverse, inclusive models perform worse than narrow models.
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fairness can still be the victim of competitive pressures in academia and industry. The flawed Bard and Bing chatbots from Google and Microsoft are recent evidence of this grim reality. The commercial necessity of building market share led to the premature release of these systems.
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William Davies · How many words does it take to make a mistake? Education, Ed... - 0 views
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The problem waiting round the corner for universities is essays generated by AI, which will leave a textual pattern-spotter like Turnitin in the dust. (Earlier this year, I came across one essay that felt deeply odd in some not quite human way, but I had no tangible evidence that anything untoward had occurred, so that was that.)
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To accuse someone of plagiarism is to make a moral charge regarding intentions. But establishing intent isn’t straightforward. More often than not, the hearings bleed into discussions of issues that could be gathered under the heading of student ‘wellbeing’, which all universities have been struggling to come to terms with in recent years.
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I have heard plenty of dubious excuses for acts of plagiarism during these hearings. But there is one recurring explanation which, it seems to me, deserves more thoughtful consideration: ‘I took too many notes.’ It isn’t just students who are familiar with information overload, one of whose effects is to morph authorship into a desperate form of curatorial management, organising chunks of text on a screen. The discerning scholarly self on which the humanities depend was conceived as the product of transitions between spaces – library, lecture hall, seminar room, study – linked together by work with pen and paper. When all this is replaced by the interface with screen and keyboard, and everything dissolves into a unitary flow of ‘content’, the identity of the author – as distinct from the texts they have read – becomes harder to delineate.
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ChatGPT Is Nothing Like a Human, Says Linguist Emily Bender - 0 views
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Please do not conflate word form and meaning. Mind your own credulity.
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We’ve learned to make “machines that can mindlessly generate text,” Bender told me when we met this winter. “But we haven’t learned how to stop imagining the mind behind it.”
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A handful of companies control what PricewaterhouseCoopers called a “$15.7 trillion game changer of an industry.” Those companies employ or finance the work of a huge chunk of the academics who understand how to make LLMs. This leaves few people with the expertise and authority to say, “Wait, why are these companies blurring the distinction between what is human and what’s a language model? Is this what we want?”
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