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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

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.

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.

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

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

The open model of participation calls into question where value is created in the education system. Gutenberg created a means to duplicate content. The social web creates the opportunity for many-to-many interactions and to add a global social layer on content creation and knowledge growth.

Whatever can be easily duplicated cannot serve as the foundation for economic value. Integration and connectedness are economic value points.

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.

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)

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.

Such a broad generalization based on one narrowly defined study, along with the suggestion that college students should be unconcerned about how much time they spend on SNS, is, at best, naive and, at worst, irresponsible.

Will there soon be a study determining that partying had no effect on grades, despite "how often students used them or how many they used"?

An hour of study tonight, an hour on the weekend, another session a week from now: such so-called spacing improves later recall, without requiring students to put in more overall study effort or pay more attention, dozens of studies have found.

“The idea is that forgetting is the friend of learning,” said Dr. Kornell. “When you forget something, it allows you to relearn, and do so effectively, the next time you see it.”

cognitive scientists see testing itself — or practice tests and quizzes — as a powerful tool of learning, rather than merely assessment. The process of retrieving an idea is not like pulling a book from a shelf; it seems to fundamentally alter the way the information is subsequently stored, making it far more accessible in the future.

“Testing not only measures knowledge but changes it,” he says — and, happily, in the direction of more certainty, not less.

“Testing has such bad connotation; people think of standardized testing or teaching to the test,” Dr. Roediger said. “Maybe we need to call it something else, but this is one of the most powerful learning tools we have.”

The harder it is to remember something, the harder it is to later forget. This effect, which researchers call “desirable difficulty,”

all I need is two columns: the most recent Tweets from everyone I follow (the standard) and the the most interesting tweets I need to pay attention to.  Recent and Interesting.  This second column is the tricky one.  It needs to be automatically generated and personalized to my interests at that moment.

search is broken on Twitter.  Unless you know the exact word you are looking for, Tweets with related terms won’t show up.  And there is no way to sort searches by relevance, it is just sorted by chronology.

Jarvis never broaches such subtleties. His is a simple world:

why not consider the possibility that the incumbents may be using the same tools, Jarvis’s revered technologies, to tell us what to think, and far more effectively than before? Internet shelf space may be infinite, but human attention is not. Cheap self-publishing marginally improves one’s chances of being heard, but nothing about this new decentralized public sphere suggests that old power structures—provided they are smart and willing to survive—will not be able to use it to their benefit

Jarvis 1.0 was all about celebrating Google, but Jarvis 2.0 has new friends in Facebook and Twitter. (An Internet intellectual always keeps up.) Jarvis 1.0 wrote that “Google’s moral of universal empowerment is the sometimes-forgotten ideal of democracy,” and argued that the company “provides the infrastructure for a culture of choice,” while its “algorithms and its business model work because Google trusts us.” Jarvis 2.0 claims that “by sharing publicly, we people challenge Google’s machines and reclaim our authority on the internet from algorithms.”

Jarvis has another reference point, another sacred telos: the equally grand and equally inexorable march of the Internet, which in his view is a technology that generates its own norms, its own laws, its own people. (He likes to speak of “us, people of the Net.”) For the Technology Man, the Internet is the glue that holds our globalized world together and the divine numen that fills it with meaning. If you thought that ethnocentrism was bad, brace yourself for Internet-centrism

Why worry about the growing dominance of such digitalism? The reason should be obvious. As Internet-driven explanations crowd out everything else, our entire vocabulary is being re-defined. Collaboration is re-interpreted through the prism of Wikipedia; communication, through the prism of social networking; democratic participation, through the prism of crowd-sourcing; cosmopolitanism, through the prism of reading the blogs of exotic “others”; political upheaval, through the prism of the so-called Twitter revolutions. Even the persecution of dissidents is now seen as an extension of online censorship (rather than the other way around). A recent headline on the blog of the Harvard-based Herdictproject—it tracks Internet censorship worldwide—announces that, in Mexico and Morocco, “Online Censorship Goes Offline.” Were activists and dissidents never harassed before Twitter and Facebook?

Most Internet intellectuals simply choose a random point in the distant past—the honor almost invariably goes to the invention of the printing press—and proceed to draw a straight line from Gutenberg to Zuckerberg, as if the Counter-Reformation, the Thirty Years’ War, the Reign of Terror, two world wars—and everything else—never happened.

even their iPad is of interest to them only as a “platform”—another buzzword of the incurious—and not as an artifact that is assembled in dubious conditions somewhere in East Asian workshops so as to produce cultic devotion in its more fortunate owners. This lack of elementary intellectual curiosity is the defining feature of the Internet intellectual. History, after all, is about details, but no Internet intellectual wants to be accused of thinking small. And so they think big—sloppily, ignorantly, pretentiously, and without the slightest appreciation of the difference between critical thought and market propaganda.

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.