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Google and Meta moved cautiously on AI. Then came OpenAI's ChatGPT. - The Washington Post - 0 views

  • The surge of attention around ChatGPT is prompting pressure inside tech giants including Meta and Google to move faster, potentially sweeping safety concerns aside
  • Tech giants have been skittish since public debacles like Microsoft’s Tay, which it took down in less than a day in 2016 after trolls prompted the bot to call for a race war, suggest Hitler was right and tweet “Jews did 9/11.”
  • Some AI ethicists fear that Big Tech’s rush to market could expose billions of people to potential harms — such as sharing inaccurate information, generating fake photos or giving students the ability to cheat on school tests — before trust and safety experts have been able to study the risks. Others in the field share OpenAI’s philosophy that releasing the tools to the public, often nominally in a “beta” phase after mitigating some predictable risks, is the only way to assess real world harms.
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  • Silicon Valley’s sudden willingness to consider taking more reputational risk arrives as tech stocks are tumbling
  • A chatbot that pointed to one answer directly from Google could increase its liability if the response was found to be harmful or plagiarized.
  • AI has been through several hype cycles over the past decade, but the furor over DALL-E and ChatGPT has reached new heights.
  • Soon after OpenAI released ChatGPT, tech influencers on Twitter began to predict that generative AI would spell the demise of Google search. ChatGPT delivered simple answers in an accessible way and didn’t ask users to rifle through blue links. Besides, after a quarter of a century, Google’s search interface had grown bloated with ads and marketers trying to game the system.
  • Inside big tech companies, the system of checks and balances for vetting the ethical implications of cutting-edge AI isn’t as established as privacy or data security. Typically teams of AI researchers and engineers publish papers on their findings, incorporate their technology into the company’s existing infrastructure or develop new products, a process that can sometimes clash with other teams working on responsible AI over pressure to see innovation reach the public sooner.
  • Chatbots like OpenAI routinely make factual errors and often switch their answers depending on how a question is asked
  • To Timnit Gebru, executive director of the nonprofit Distributed AI Research Institute, the prospect of Google sidelining its responsible AI team doesn’t necessarily signal a shift in power or safety concerns, because those warning of the potential harms were never empowered to begin with. “If we were lucky, we’d get invited to a meeting,” said Gebru, who helped lead Google’s Ethical AI team until she was fired for a paper criticizing large language models.
  • Rumman Chowdhury, who led Twitter’s machine-learning ethics team until Elon Musk disbanded it in November, said she expects companies like Google to increasingly sideline internal critics and ethicists as they scramble to catch up with OpenAI.“We thought it was going to be China pushing the U.S., but looks like it’s start-ups,” she said.
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CRITICAL AI: Adapting College Writing for the Age of Large Language Models such as Chat... - 1 views

  • In the long run, we believe, teachers need to help students develop a critical awareness of generative machine models: how they work; why their content is often biased, false, or simplistic; and what their social, intellectual, and environmental implications might be. But that kind of preparation takes time, not least because journalism on this topic is often clickbait-driven, and “AI” discourse tends to be jargony, hype-laden, and conflated with science fiction.
  • Make explicit that the goal of writing is neither a product nor a grade but, rather, a process that empowers critical thinking
  • No one should present auto-generated writing as their own on the expectation that this deception is undiscoverable. 
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  • LLMs usually cannot do a good job of explaining how a particular passage from a longer text illuminates the whole of that longer text. Moreover, ChatGPT’s outputs on comparison and contrast are often superficial. Typically the system breaks down a task of logical comparison into bite-size pieces, conveys shallow information about each of those pieces, and then formulaically “compares” and “contrasts” in a noticeably superficial or repetitive way. 
  • In-class writing, whether digital or handwritten, may have downsides for students with anxiety and disabilities
  • ChatGPT can produce outputs that take the form of  “brainstorms,” outlines, and drafts. It can also provide commentary in the style of peer review or self-analysis. Nonetheless, students would need to coordinate multiple submissions of automated work in order to complete this type of assignment with a text generator.  
  • Students are more likely to misuse text generators if they trust them too much. The term “Artificial Intelligence” (“AI”) has become a marketing tool for hyping products. For all their impressiveness, these systems are not intelligent in the conventional sense of that term. They are elaborate statistical models that rely on mass troves of data—which has often been scraped indiscriminately from the web and used without knowledge or consent.
  • LLMs often mimic the harmful prejudices, misconceptions, and biases found in data scraped from the internet
  • Show students examples of inaccuracy, bias, logical, and stylistic problems in automated outputs. We can build students’ cognitive abilities by modeling and encouraging this kind of critique. Given that social media and the internet are full of bogus accounts using synthetic text, alerting students to the intrinsic problems of such writing could be beneficial. (See the “ChatGPT/LLM Errors Tracker,” maintained by Gary Marcus and Ernest Davis.)
  • Since ChatGPT is good at grammar and syntax but suffers from formulaic, derivative, or inaccurate content, it seems like a poor foundation for building students’ skills and may circumvent their independent thinking.
  • Good journalism on language models is surprisingly hard to find since the technology is so new and the hype is ubiquitous. Here are a few reliable short pieces.     “ChatGPT Advice Academics Can Use Now” edited by Susan Dagostino, Inside Higher Ed, January 12, 2023  “University students recruit AI to write essays for them. Now what?” by Katyanna Quach, The Register, December 27, 2022  “How to spot AI-generated text” by Melissa Heikkilä, MIT Technology Review, December 19, 2022  The Road to AI We Can Trust, Substack by Gary Marcus, a cognitive scientist and AI researcher who writes frequently and lucidly about the topic. See also Gary Marcus and Ernest Davis, “GPT-3, Bloviator: OpenAI’s Language Generator Has No Idea What It’s Talking About” (2020).
  • “On the Dangers of Stochastic Parrots” by Emily M. Bender, Timnit Gebru, et al, FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, March 2021. Association for Computing Machinery, doi: 10.1145/3442188. A blog post summarizing and discussing the above essay derived from a Critical AI @ Rutgers workshop on the essay: summarizes key arguments, reprises discussion, and includes links to video-recorded presentations by digital humanist Katherine Bode (ANU) and computer scientist and NLP researcher Matthew Stone (Rutgers).
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The Myth Of AI | Edge.org - 0 views

  • The distinction between a corporation and an algorithm is fading. Does that make an algorithm a person? Here we have this interesting confluence between two totally different worlds. We have the world of money and politics and the so-called conservative Supreme Court, with this other world of what we can call artificial intelligence, which is a movement within the technical culture to find an equivalence between computers and people. In both cases, there's an intellectual tradition that goes back many decades. Previously they'd been separated; they'd been worlds apart. Now, suddenly they've been intertwined.
  • Since our economy has shifted to what I call a surveillance economy, but let's say an economy where algorithms guide people a lot, we have this very odd situation where you have these algorithms that rely on big data in order to figure out who you should date, who you should sleep with, what music you should listen to, what books you should read, and on and on and on. And people often accept that because there's no empirical alternative to compare it to, there's no baseline. It's bad personal science. It's bad self-understanding.
  • there's no way to tell where the border is between measurement and manipulation in these systems
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  • It's not so much a rise of evil as a rise of nonsense. It's a mass incompetence, as opposed to Skynet from the Terminator movies. That's what this type of AI turns into.
  • What's happened here is that translators haven't been made obsolete. What's happened instead is that the structure through which we receive the efforts of real people in order to make translations happen has been optimized, but those people are still needed.
  • because of the mythology about AI, the services are presented as though they are these mystical, magical personas. IBM makes a dramatic case that they've created this entity that they call different things at different times—Deep Blue and so forth. The consumer tech companies, we tend to put a face in front of them, like a Cortana or a Siri
  • If you talk to translators, they're facing a predicament, which is very similar to some of the other early victim populations, due to the particular way we digitize things. It's similar to what's happened with recording musicians, or investigative journalists—which is the one that bothers me the most—or photographers. What they're seeing is a severe decline in how much they're paid, what opportunities they have, their long-term prospects.
  • In order to create this illusion of a freestanding autonomous artificial intelligent creature, we have to ignore the contributions from all the people whose data we're grabbing in order to make it work. That has a negative economic consequence.
  • If you talk about AI as a set of techniques, as a field of study in mathematics or engineering, it brings benefits. If we talk about AI as a mythology of creating a post-human species, it creates a series of problems that I've just gone over, which include acceptance of bad user interfaces, where you can't tell if you're being manipulated or not, and everything is ambiguous. It creates incompetence, because you don't know whether recommendations are coming from anything real or just self-fulfilling prophecies from a manipulative system that spun off on its own, and economic negativity, because you're gradually pulling formal economic benefits away from the people who supply the data that makes the scheme work.
  • This idea that some lab somewhere is making these autonomous algorithms that can take over the world is a way of avoiding the profoundly uncomfortable political problem, which is that if there's some actuator that can do harm, we have to figure out some way that people don't do harm with it. There are about to be a whole bunch of those. And that'll involve some kind of new societal structure that isn't perfect anarchy. Nobody in the tech world wants to face that, so we lose ourselves in these fantasies of AI. But if you could somehow prevent AI from ever happening, it would have nothing to do with the actual problem that we fear, and that's the sad thing, the difficult thing we have to face.
  • To reject your own ignorance just casts you into a silly state where you're a lesser scientist. I don't see that so much in the neuroscience field, but it comes from the computer world so much, and the computer world is so influential because it has so much money and influence that it does start to bleed over into all kinds of other things.
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William Davies · How many words does it take to make a mistake? Education, Ed... - 0 views

  • 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.)
  • 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.
  • 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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  • This generation, the first not to have known life before the internet, has acquired a battery of skills in navigating digital environments, but it isn’t clear how well those skills line up with the ones traditionally accredited by universities.
  • From the perspective of students raised in a digital culture, the anti-plagiarism taboo no doubt seems to be just one more academic hang-up, a weird injunction to take perfectly adequate information, break it into pieces and refashion it. Students who pay for essays know what they are doing; others seem conscientious yet intimidated by secondary texts: presumably they won’t be able to improve on them, so why bother trying? For some years now, it’s been noticeable how many students arrive at university feeling that every interaction is a test they might fail. They are anxious. Writing seems fraught with risk, a highly complicated task that can be executed correctly or not.
  • Many students may like the flexibility recorded lectures give them, but the conversion of lectures into yet more digital ‘content’ further destabilises traditional conceptions of learning and writing
  • the evaluation forms which are now such a standard feature of campus life suggest that many students set a lot of store by the enthusiasm and care that are features of a good live lecture
  • the drift of universities towards a platform model, which makes it possible for students to pick up learning materials as and when it suits them. Until now, academics have resisted the push for ‘lecture capture’. It causes in-person attendance at lectures to fall dramatically, and it makes many lecturers feel like mediocre television presenters. Unions fear that extracting and storing teaching for posterity threatens lecturers’ job security and weakens the power of strikes. Thanks to Covid, this may already have happened.
  • This vision of language as code may already have been a significant feature of the curriculum, but it appears to have been exacerbated by the switch to online teaching. In a journal article from August 2020, ‘Learning under Lockdown: English Teaching in the Time of Covid-19’, John Yandell notes that online classes create wholly closed worlds, where context and intertextuality disappear in favour of constant instruction. In these online environments, readingis informed not by prior reading experiences but by the toolkit that the teacher has provided, and ... is presented as occurring along a tramline of linear development. Different readings are reducible to better or worse readings: the more closely the student’s reading approximates to the already finalised teacher’s reading, the better it is. That, it would appear, is what reading with precision looks like.
  • an injunction against creative interpretation and writing, a deprivation that working-class children will feel at least as deeply as anyone else.
  • There may be very good reasons for delivering online teaching in segments, punctuated by tasks and feedback, but as Yandell observes, other ways of reading and writing are marginalised in the process. Without wishing to romanticise the lonely reader (or, for that matter, the lonely writer), something is lost when alternating periods of passivity and activity are compressed into interactivity, until eventually education becomes a continuous cybernetic loop of information and feedback. How many keystrokes or mouse-clicks before a student is told they’ve gone wrong? How many words does it take to make a mistake?
  • In the utopia sold by the EdTech industry (the companies that provide platforms and software for online learning), pupils are guided and assessed continuously. When one task is completed correctly, the next begins, as in a computer game; meanwhile the platform providers are scraping and analysing data from the actions of millions of children. In this behaviourist set-up, teachers become more like coaches: they assist and motivate individual ‘learners’, but are no longer so important to the provision of education. And since it is no longer the sole responsibility of teachers or schools to deliver the curriculum, it becomes more centralised – the latest front in a forty-year battle to wrest control from the hands of teachers and local authorities.
  • Constant interaction across an interface may be a good basis for forms of learning that involve information-processing and problem-solving, where there is a right and a wrong answer. The cognitive skills that can be trained in this way are the ones computers themselves excel at: pattern recognition and computation. The worry, for anyone who cares about the humanities in particular, is about the oversimplifications required to conduct other forms of education in these ways.
  • Blanket surveillance replaces the need for formal assessment.
  • Confirming Adorno’s worst fears of the ‘primacy of practical reason’, reading is no longer dissociable from the execution of tasks. And, crucially, the ‘goals’ to be achieved through the ability to read, the ‘potential’ and ‘participation’ to be realised, are economic in nature.
  • since 2019, with the Treasury increasingly unhappy about the amount of student debt still sitting on the government’s balance sheet and the government resorting to ‘culture war’ at every opportunity, there has been an effort to single out degree programmes that represent ‘poor value for money’, measured in terms of graduate earnings. (For reasons best known to itself, the usually independent Institute for Fiscal Studies has been leading the way in finding correlations between degree programmes and future earnings.) Many of these programmes are in the arts and humanities, and are now habitually referred to by Tory politicians and their supporters in the media as ‘low-value degrees’.
  • studying the humanities may become a luxury reserved for those who can fall back on the cultural and financial advantages of their class position. (This effect has already been noticed among young people going into acting, where the results are more visible to the public than they are in academia or heritage organisations.)
  • given the changing class composition of the UK over the past thirty years, it’s not clear that contemporary elites have any more sympathy for the humanities than the Conservative Party does. A friend of mine recently attended an open day at a well-known London private school, and noticed that while there was a long queue to speak to the maths and science teachers, nobody was waiting to speak to the English teacher. When she asked what was going on, she was told: ‘I’m afraid parents here are very ambitious.’ Parents at such schools, where fees have tripled in real terms since the early 1980s, tend to work in financial and business services themselves, and spend their own days profitably manipulating and analysing numbers on screens. When it comes to the transmission of elite status from one generation to the next, Shakespeare or Plato no longer has the same cachet as economics or physics.
  • Leaving aside the strategic political use of terms such as ‘woke’ and ‘cancel culture’, it would be hard to deny that we live in an age of heightened anxiety over the words we use, in particular the labels we apply to people. This has benefits: it can help to bring discriminatory practices to light, potentially leading to institutional reform. It can also lead to fruitless, distracting public arguments, such as the one that rumbled on for weeks over Angela Rayner’s description of Conservatives as ‘scum’. More and more, words are dredged up, edited or rearranged for the purpose of harming someone. Isolated words have acquired a weightiness in contemporary politics and public argument, while on digital media snippets of text circulate without context, as if the meaning of a single sentence were perfectly contained within it, walled off from the surrounding text. The exemplary textual form in this regard is the newspaper headline or corporate slogan: a carefully curated series of words, designed to cut through the blizzard of competing information.
  • Visit any actual school or university today (as opposed to the imaginary ones described in the Daily Mail or the speeches of Conservative ministers) and you will find highly disciplined, hierarchical institutions, focused on metrics, performance evaluations, ‘behaviour’ and quantifiable ‘learning outcomes’.
  • If young people today worry about using the ‘wrong’ words, it isn’t because of the persistence of the leftist cultural power of forty years ago, but – on the contrary – because of the barrage of initiatives and technologies dedicated to reversing that power. The ideology of measurable literacy, combined with a digital net that has captured social and educational life, leaves young people ill at ease with the language they use and fearful of what might happen should they trip up.
  • It has become clear, as we witness the advance of Panopto, Class Dojo and the rest of the EdTech industry, that one of the great things about an old-fashioned classroom is the facilitation of unrecorded, unaudited speech, and of uninterrupted reading and writing.
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How to Turn Your Syllabus into an Infographic - The Visual Communication Guy - 0 views

  • If you’re ever going to turn a syllabus into an infographic, you must, MUST reduce the amount of text you are using. There are, of course, important things you’ll want and must include, but you can’t think of this document as ten pages of paragraphs. Strip down to only the essential information, with a bit of added info where you  think some flare or excitement is needed. Remember: your students are smart people. They can understand documents quickly without a bunch of extra fluff, so remove all the unnecessary stuff.
  • Once you’ve determined the sections, it’s easier to think about what relates to what and how you might organize your syllabus in a way that makes sense for your students.
  • try drawing it out on sketch paper first. While this will seem like an annoying task for most people, trust me when I say that it will save you a lot of time in the long run
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  • If there is anything on your syllabus that can be quantified (like percentages for grades or assignments), consider making bar graphs or pie charts to visually represent it. This is helpful, too, so students can visually understand, very quickly, how much weight is given to each project.
  • Remember to only use pictures that you either created yourself (own the copyright) or that you found through creative commons or public domain websites. Don’t use ugly clipart or images that you don’t have permission to use. A great place to find free icons? Flaticon.com.
  • Remember to reduce as much text as possible and supplement what you write with an image. Consider using the images of your required textbooks, for example, and use icons and graphics that relate to each section.
  • Adobe InDesign
  • Don’t get so caught up in designing a cool infographic about your course that you forget to include information about accessibility, Title IX, academic dishonesty, and other related information. I might recommend not going too fancy on the institution-wide policies. You might still keep that in paragraph form, just so that there is no way to misinterpret what your institution wants you to say.
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9 Ways Online Teaching Should be Different from Face-to-Face | Cult of Pedagogy - 0 views

  • Resist the temptation to dive right into curriculum at the start of the school year. Things will go more smoothly if you devote the early weeks to building community so students feel connected. Social emotional skills can be woven in during this time. On top of that, students need practice with whatever digital tools you’ll be using. So focus your lessons on those things, intertwining the two when possible. 
  • Online instruction is made up largely of asynchronous instruction, which students can access at any time. This is ideal, because requiring attendance for synchronous instruction puts some students at an immediate disadvantage if they don’t have the same access to technology, reliable internet, or a flexible home schedule. 
  • you’re likely to offer “face-to-face” or synchronous opportunities at some point, and one way to make them happen more easily is to have students meet in small groups. While it’s nearly impossible to arrange for 30 students to attend a meeting at once, assigning four students to meet is much more manageable.
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  • What works best, Kitchen says, is to keep direct instruction—things like brief video lectures and readings—in asynchronous form, using checks for understanding like embedded questions or exit slips.  You can then use synchronous meetings for more interactive, engaging work. “If we want students showing up, if we want them to know that this is worth their time,” Kitchen explains, “it really needs to be something active and engaging for them. Any time they can work with the material, categorize it, organize it, share further thoughts on it, have a discussion, all of those are great things to do in small groups.” 
  • The Jigsaw method, where students form expert groups on a particular chunk of content, then teach that content to other students. Discussion strategies adapted for virtual settingsUsing best practices for cooperative learning Visible Thinking routinesGamestorming and other business related protocols adapted for education, where students take on the role of customers/stakeholders
  • Online instruction is not conducive to covering large amounts of content, so you have to choose wisely, teaching the most important things at a slower pace.
  • What really holds leverage for the students? What has endurance? What knowledge is essential?What knowledge and skills do students need to have before they move to the next grade level or the next class?What practices can be emphasized that transfer across many content areas?  Skills like analyzing, constructing arguments, building a strong knowledge base through texts, and speaking can all be taught through many different subjects. What tools can serve multiple purposes? Teaching students to use something like Padlet gives them opportunities to use audio, drawing, writing, and video. Non-digital tools can also work: Students can use things they find around the house, like toilet paper rolls, to fulfill other assignments, and then submit their work with a photo.
  • Provide instructions in a consistent location and at a consistent time. This advice was already given for parents, but it’s worth repeating here through the lens of instructional design: Set up lessons so that students know where to find instructions every time. Make instructions explicit. Read and re-read to make sure these are as clear as possible. Make dogfooding your lessons a regular practice to root out problem areas.Offer multimodal instructions. If possible, provide both written and video instructions for assignments, so students can choose the format that works best for them. You might also offer a synchronous weekly or daily meeting; what’s great about doing these online is that even if you teach several sections of the same class per day, students are no longer restricted to class times and can attend whatever meeting works best for them.
  • put the emphasis on formative feedback as students work through assignments and tasks, rather than simply grading them at the end. 
  • In online learning, Kitchen says, “There are so many ways that students can cheat, so if we’re giving them just the traditional quiz or test, it’s really easy for them to be able to just look up that information.” A great solution to this problem is to have students create things.
  • For assessment, use a detailed rubric that highlights the learning goals the end product will demonstrate. A single-point rubric works well for this.To help students discover tools to work with, this list of tools is organized by the type of product each one creates. Another great source of ideas is the Teacher’s Guide to Tech.When developing the assignment, rather than focusing on the end product, start by getting clear on what you want students to DO with that product.
  • Clear and consistent communicationCreating explicit and consistent rituals and routinesUsing research-based instructional strategiesDetermining whether to use digital or non-digital tools for an assignment A focus on authentic learning, where authentic products are created and students have voice and choice in assignments
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Lurching Toward Fall, Disaster on the Horizon | Just Visiting - 0 views

  • the virus will be far more present in far more places when school starts in August than it was when most schools shut down in March
  • I am among the crowd who both believes that online learning can be done quite well, and that there is something irreplaceable about the experiences of face-to-face learning, when that learning is happening under reasonable conditions that is. These are not reasonable conditions. Do not get me wrong. This is a loss. The experience of community is not the same at a distance or over the internet. It is not necessarily entirely absent, but it is not as present.
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How much 'work' should my online course be for me and my students? - Dave's Educational... - 0 views

  • My recommendation for people planning their courses, is to stop thinking about ‘contact hours’. A contact hour is a constraint that is applied to the learning process because of the organizational need to have people share a space in a building. Also called a credit hour, (particularly for American universities) this has meant, from a workload perspective, that for every in class hour a student is meant to do at least 2 (in some cases 3) hours of study outside of class. Even Cliff Notes agrees with me. So… for a full load, that 30 to 45 Total Work Hours for students per course that you are designing.
  • Simple break down (not quite 90, yes i know) Watch 3 hours of video* – 5 hoursRead stuff – 20 hoursListen to me talk – 15 hoursTalk with other students in a group – 15 hoursWrite reflections about group chat – 7.5 hoursRespond to other people’s reflections – 7.5 hoursWork on a term paper – 10 hoursDo weekly quiz – 3 hoursWrite take home mid-term – 3 hoursWrite take home final – 3 hours
  • A thousand variations of this might be imagined
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  • a possible structure recommended by one of the faculty we were talking to was – read/watch, quiz, lecture, student group discussion, reflection. The reasoning here is that if you give learners (particularly new learners) a reading without some form of accountability (a quiz) they are much less likely to do it. I know that for me, when I’ve done the readings, I’m far more likely to attend class. Putting the student group discussion after the lecture gives students who can’t attend a synchronous session a chance to review the recording
  • The standardization police have been telling us for years that each student must learn the same things. Poppycock. Scaffolding doesn’t mean taking away student choice. There are numerous approaches to allowing a little or a lot of choice into your classes (learner contracts come to mind). Just remember, most students don’t want choice – at first. 12-16 years of training has told them that you the faculty member have something you want them to do and they need to find the trick of it. It will take a while until those students actually believe you want their actual opinion.
  • You can have a goal like – get them acculturated to the field – and work through your activities to get there. It’s harder, they will need your patience, but once they get their minds around it, it makes things much more interesting.
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About That Webcam Obsession You're Having… | Reflecting Allowed - 0 views

  • About that obsession you’ve got with students turning on their cameras during class. I understand why you’ve got it. I’d like to help you deal with it. I say “deal with it” because many students complain to me that they don’t like being forced to turn their cameras on
  • it’s probably essential to our wellbeing to see human faces. As a teacher and presenter and facilitator, seeing facial expressions and reactions of audience/participants makes a huge difference. I get it. I get that you need to know someone is listening, and see those reactions. I get it. I recently gave a keynote and asked a few friends to be on webinar panel so I could see their smiling faces. However, when I am in a position of power like in the class, I never ask students to turn on their cameras. And my students were *almost always all engaged* last semester in our Zoom calls.
  • You can’t make eye contact online
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  • Reasons why people want to keep their cameras off include: Discomfort or shyness with showing their faces online. This is real, people. For most people, it gets better with time, but not always and not in every context.Noisy or busy home environments e.g. spouse or kids or siblings moving about. I have occasionally had to mute and turn camera off in the middle of a webinar I am personally giving for those reasons! Women and girls can be especially vulnerable to kids and spouses not respecting their work/learning timeNot being dressed for company (for me personally, I often don’t want to cover my hair for a meeting where I’m not presenting, I want to lounge around in comfy clothes). Or your home not being tidy enough for company. This is a thing.Slow/unstable internet connection. Turning off webcam can be the easiest way to get better quality audioDiscomfort over recording
  • Ask questions and ask everyone to respond in the chat. You will know if they are focused and engaged by their responses and every single person can participateAsk questions for them to answer orally. Either call on people round robin, or call out some people from the chat (also keeping in mind some people are voice shy, and some people have noisy home environments)If you can divide students into smaller groups go talk to each other and you can move between them like a butterfly, this can help some people engage/talk more and occasionally even turn their cameras onUse things like Annotation or Google docs to have folks contributeAsk students to have a profile picture up when their camera is off. This helps sometimes.You might learn to distinguish student voices as you would close friends on the phone (remember life pre-caller ID where close friends and family would expect that?) and use them as proxies for how they are feeling. You already have this skill, but are not expecting to use it.If you record, consider having an unrecorded portion. You will be surprised how much some people participate or are willing to turn cameras on in the unrecorded portion.
  • it seems we need to consider ways of allowing people to “be there” in alternative ways that they are comfortable with and that tell us they are really listening to us and responding in more explicit ways
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The Ed-Tech Imaginary - 0 views

  • We can say "Black lives matter," but we must also demonstrate through our actions that Black lives matter, and that means we must radically alter many of our institutions and practices, recognizing their inhumanity and carcerality. And that includes, no doubt, ed-tech. How much of ed-tech is, to use Ruha Benjamin's phrase, "the new Jim Code"? How much of ed-tech is designed by those who imagine students as cheats or criminals, as deficient or negligent?
  • "Reimagining" is a verb that education reformers are quite fond of. And "reimagining" seems too often to mean simply defunding, privatizing, union-busting, dismantling, outsourcing.
  • if Betsy DeVos is out there "reimagining," then we best be resisting
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  • think we can view the promotion of ed-tech as a similar sort of process — the stories designed to convince us that the future of teaching and learning will be a technological wonder. The "jobs of the future that don't exist yet." The push for everyone to "learn to code."
  • The Matrix is, after all, a dystopia. So why would Matrix-style learning be desirable? Maybe that's the wrong question. Perhaps it's not so much that it's desirable, but it's just how our imaginations have been constructed, constricted even. We can't imagine any other ideal but speed and efficiency.
  • The first science fiction novel, published over 200 years ago, was in fact an ed-tech story: Mary Shelley's Frankenstein. While the book is commonly interpreted as a tale of bad science, it is also the story of bad education — something we tend to forget if we only know the story through the 1931 film version
  • This ed-tech imaginary is segregated. There are no Black students at the push-button school. There are no Black people in The Jetsons — no Black people living the American dream of the mid-twenty-first century
  • we must also decolonize the ed-tech imaginary
  • Zuckerberg gave everyone at Facebook a copy of the Ernest Cline novel Ready Player One, for example, to get them excited about building technology for the future — a book that is really just a string of nostalgic references to Eighties white boy culture. And I always think about that New York Times interview with Sal Khan, where he said that "The science fiction books I like tend to relate to what we're doing at Khan Academy, like Orson Scott Card's 'Ender's Game' series." You mean, online math lectures are like a novel that justifies imperialism and genocide?! Wow.
  • Teaching machines and robot teachers were part of the Sixties' cultural imaginary — perhaps that's the problem with so many Boomer ed-reform leaders today. But that imaginary — certainly in the case of The Jetsons — was, upon close inspection, not always particularly radical or transformative. The students at Little Dipper Elementary still sat in desks in rows. The teacher still stood at the front of the class, punishing students who weren't paying attention.
  • Part of the argument I make in my book is that much of education technology has been profoundly shaped by Skinner, even though I'd say that most practitioners today would say that they reject his theories; that cognitive science has supplanted behaviorism; and that after Ayn Rand and Noam Chomsky trashed Beyond Freedom and Dignity, no one paid attention to Skinner any more — which is odd considering there are whole academic programs devoted to "behavioral design," bestselling books devoted to the "nudge," and so on.
  • so much of the ed-tech imaginary is wrapped up in narratives about the Hero, the Weapon, the Machine, the Behavior, the Action, the Disruption. And it's so striking because education should be a practice of care, not conquest
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Offering Seminar Courses Remotely | Educatus - 0 views

  • In an online environment, seminars will work best if they occur asynchronously in the discussion boards in an LMS
  • The 4 key elements for a seminar that need to be replicated during remote instruction include: A prompt or text(s) that the student considers independently in advance Guiding questions that require analysis, synthesize and/or evaluation of ideas The opportunity to share personal thinking with a group Ideas being developed, rejected, and refined over time based on everyone’s contributions
  • Students need specific guidance and support for how to develop, reject, and refine ideas appropriately in your course.  If you want students to share well, consider requiring an initial post where you and students introduce yourselves and share a picture. Describe your expectations for norms in how everyone will behave online Provide a lot of initial feedback about the quality of posting.  Consider giving samples of good and bad posts, and remember to clarify your marking criteria. Focus your expectations on the quality of comments, and set maximums for the amount you expect to reduce your marking load and keep the discussions high quality. Someone will need to moderate the discussion. That includes posting the initial threads, reading what everyone posts all weeks and commenting to keep the discussion flowing.  Likely, the same person (you or a TA) will also be grading and providing private feedback to each student. Consider making the moderation of a discussion an assignment in your course. You can moderate the first few weeks to demonstrate what you want, and groups of students can moderate other weeks. It can increase engagement if done well, and definitely decreases your work load.
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  • Teach everyone to mute when not speaking, and turn off their cameras if they have bandwidth issues. Use the chat so people can agree and add ideas as other people are speaking, and teach people to raise their hands or add emoticons in the participants window to help you know who wants to speak next
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