2,071 Matching Annotations
  1. Sep 2016
    1. We need to recognize that many students who are not ready for an exam on October 15 might succeed on November 1.

      According to some, this is the core shift needed to make Competency-Based Education (CBE) work, in practice. The idea isn’t to sort people out by testing everyone at the same time but to allow people to develop the needed competencies at their own pace. In fact, some discussions of CBE revolve around the notion that a learner failing an exam demonstrates that it wasn’t administered at the right time. May sound really strange in the current system for formal education but there are plenty of similar models outside of formal education, including in (at least the popular culture version of) martial arts.

    1. The queue of electronic hands could take so long to get through that some students abandoned hope and lowered their hands while others got into the habit of raising their hand pre-emptively just so they’d have a spot in line if an idea came into their head later on.
    1. L’enseignant joue quatre rôles distincts : celui de client, qui juge l’adéquation du produit au cahier des charges, celui d’expert technique, en cas de difficulté bloquante, celui de chef d’entreprise lorsque cela s’impose et que des décisions autoritaires (concernant les coûts, les délais ou les méthodes) doivent être prises pour empêcher l’échec du projet, et enfin le rôle traditionnel de tuteur.
    2. Pour leur faciliter la tâche, lorsqu’un enseignant dispense un cours magistral, un autre enseignant est présent dans la salle et joue un double rôle : il apporte éventuellement des points de clarification à travers une formulation alternative et il n’hésite pas à poser des questions, parfois volontairement naïves, afin de désinhiber les élèves qui n’oseraient pas intervenir.

      Interesting approach. Puts the primary teacher’s roles in a new light.

    3. Ces méthodes, qui pourraient sembler brutales si nous n’étions pas intimement convaincus de leurs vertus pédagogiques, s’avèrent avoir un effet extrêmement bénéfique sur les étudiants.
    1. every person on earth can access and contribute to the sum of all human knowledge.

      Is it just me or the “contribute” part has largely been put aside, in the meantime?

    1. The least valuable category of device among educators was, by far, smart watches, with 59 percent saying they are either "not very valuable" (50 percent) or actually "detrimental" to education (9 percent).
    1. For the most successful ed tech rollouts, teachers have to be on board with the plan and they need training to master the new technologies before introducing them in the classroom.
    2. Interactive whiteboards were all the rage in ed tech purchases several years ago, costing schools millions of dollars but gaining little in the classroom.
    3. Survey: Teachers dislike smartphones, interactive whiteboards in classroom

      Contrast this with the THE title:

      Research: Laptops, Chromebooks and Tablets Most Valuable Education Tools, Teachers Say

    1. We commonly look at Ivy League institutions as the standard of higher education in America, but the truth is that the majority of the nation's workforce, innovation identity and manufacturing futures are tied to those institutions which graduate outside of the realm of high achievers from wealthy families. 
    1. «Les tableaux intelligents ne fonctionnent pas, mais on fait comme à l'époque, quand la lumière d'un rétroprojecteur brûlait : on sort notre craie et on utilise le tableau! Ce n'est quand même pas la fin du monde. La terre n'a pas arrêté de tourner», conclut Francis Jacob.
    1. Some of the other benefits include: Permits for peer review. Fulfills social responsibility of offering education to all. Increases standard of educational resources. Improves a university’s status and that of the researcher or educators.
    1. Take out your microphone, make some noise, and give your writing a voice.
    2. this article is particularly concerned with the ways that uncritical adoption of educational technologies adversely impacts the autonomy of students and teachers within the shared enterprise of learning
    3. narratives that pit students, teachers, and publics against one another

      Recalls one of Audrey Watters’s key points about the Blockchain in Education (based, in this case, on Neil Selwyn).

    4. it’s productive to not only think of schools and colleges as sites of learning, but also as marketplaces where goods, knowledge, and services are consumed and produced

      Agreed that it’s productive. But isn’t it also about framing (formal/institutional) education in purely economic terms? Useful to think about goods and services which have exchange value. May be a bit too easy to slip into the implicit idea that a learner is among the system’s key products.

    5. A network perspective not only lays bare the various stakeholders with a vested social, economic, and political interest in what happens within schools and colleges, but also the ways agency for what happens within classrooms at my institution extends beyond the students and educators charged with constructing learning.

      Useful approach (reminiscent of ANT), especially if paired with a community-based approach.

    6. frame the purposes and value of education in purely economic terms

      Sign of the times? One part is about economics as the discipline of decision-making. Economists often claim that their work is about any risk/benefit analysis and isn’t purely about money. But the whole thing is still about “resources” or “exchange value”, in one way or another. So, it could be undue influence from this way of thinking. A second part is that, as this piece made clear at the onset, “education is big business”. In some ways, “education” is mostly a term for a sector or market. Schooling, Higher Education, Teaching, and Learning are all related. Corporate training may not belong to the same sector even though many of the aforementioned EdTech players bet big on this. So there’s a logic to focus on the money involved in “education”. Has little to do with learning experiences, but it’s an entrenched system.

      Finally, there’s something about efficiency, regardless of effectiveness. It’s somewhat related to economics, but it’s often at a much shallower level. The kind of “your tax dollars at work” thinking which is so common in the United States. “It’s the economy, silly!”

    7. who will (and will not) control and define the learning process, who will (and will not) profit from the ways that learning processes are enacted, who will (and will not) have access to science and scholarship and the infrastructure necessary for creating it, who will (and will not) participate in the design of curriculum and assessment and learning spaces, who will (and will not) profit from the benefits of science and artistry, and who will (and will not) have opportunities to attend schools and colleges.

      Several (though not all) of these questions relate to the core sociological one: Who Decides? The list sounds, in part, like a call for deeper and more nuanced “stakeholders” thinking than the typical case study. The apparent focus (at least with parenthetical mentions of those excluded) is on the limits of inclusion. From this, we could already be thinking about community-building, especially in view of a strong Community of Practice.

    8. ownership in educational systems
    9. those most directly involved in learning

      Ha! The “stakeholders”!

    10. Foregrounding the critical role that autonomy plays within learning, Chris gestures tacitly toward the decreasing level of agency that those most directly involved in learning have in defining the processes and purposes of education on their own terms

      How wordy!

    1. captures values such as transparency and student autonomy

      Indeed. “Privacy” makes it sound like a single factor, hiding the complexity of the matter and the importance of learners’ agency.

    2. Activities such as time spent on task and discussion board interactions are at the forefront of research.

      Really? These aren’t uncontroversial, to say the least. For instance, discussion board interactions often call for careful, mixed-method work with an eye to preventing instructor effect and confirmation bias. “Time on task” is almost a codeword for distinctions between models of learning. Research in cognitive science gives very nuanced value to “time spent on task” while the Malcolm Gladwells of the world usurp some research results. A major insight behind Competency-Based Education is that it can allow for some variance in terms of “time on task”. So it’s kind of surprising that this summary puts those two things to the fore.

    3. Research: Student data are used to conduct empirical studies designed primarily to advance knowledge in the field, though with the potential to influence institutional practices and interventions. Application: Student data are used to inform changes in institutional practices, programs, or policies, in order to improve student learning and support. Representation: Student data are used to report on the educational experiences and achievements of students to internal and external audiences, in ways that are more extensive and nuanced than the traditional transcript.

      Ha! The Chronicle’s summary framed these categories somewhat differently. Interesting. To me, the “application” part is really about student retention. But maybe that’s a bit of a cynical reading, based on an over-emphasis in the Learning Analytics sphere towards teleological, linear, and insular models of learning. Then, the “representation” part sounds closer to UDL than to learner-driven microcredentials. Both approaches are really interesting and chances are that the report brings them together. Finally, the Chronicle made it sound as though the research implied here were less directed. The mention that it has “the potential to influence institutional practices and interventions” may be strategic, as applied research meant to influence “decision-makers” is more likely to sway them than the type of exploratory research we so badly need.

    1. often private companies whose technologies power the systems universities use for predictive analytics and adaptive courseware
    2. the use of data in scholarly research about student learning; the use of data in systems like the admissions process or predictive-analytics programs that colleges use to spot students who should be referred to an academic counselor; and the ways colleges should treat nontraditional transcript data, alternative credentials, and other forms of documentation about students’ activities, such as badges, that recognize them for nonacademic skills.

      Useful breakdown. Research, predictive models, and recognition are quite distinct from one another and the approaches to data that they imply are quite different. In a way, the “personalized learning” model at the core of the second topic is close to the Big Data attitude (collect all the things and sense will come through eventually) with corresponding ethical problems. Through projects vary greatly, research has a much more solid base in both ethics and epistemology than the kind of Big Data approach used by technocentric outlets. The part about recognition, though, opens the most interesting door. Microcredentials and badges are a part of a broader picture. The data shared in those cases need not be so comprehensive and learners have a lot of agency in the matter. In fact, when then-Ashoka Charles Tsai interviewed Mozilla executive director Mark Surman about badges, the message was quite clear: badges are a way to rethink education as a learner-driven “create your own path” adventure. The contrast between the three models reveals a lot. From the abstract world of research, to the top-down models of Minority Report-style predictive educating, all the way to a form of heutagogy. Lots to chew on.

    3. the ways colleges should treat nontraditional transcript data, alternative credentials, and other forms of documentation about students’ activities, such as badges, that recognize them for nonacademic skills.
    4. colleges need to "shift from a compliance mentality to a responsibility mentality."
    5. necessary to spot students at risk of dropping out or to improve teaching through so-called adaptive-learning courseware
    1. Qualitative differences like spending on recruitment or types of degrees conferred matter to solvency and public perception.
    2. mis-read or failed to read the labor market for different degree types.

      Sounds fairly damning for a business based on helping diverse students with the labour market…

    3. The aggressive recruiting did not extend to aggressive retainment and debt management.
    4. under-motivated or differently motivated students

      Intriguing categories. Would be interested in how these came up through interviews.

    5. Sociologist Dorothy Smith called this “textually-mediated social organization” or institutional ethnography.
    6. If an organization works — and extracting billions of dollars in federal student aid money suggests ITT worked for a long time — then who it most frequently and efficiently works best for is one way to understand the organization.
    7. One way to study for-profit colleges as organizations is to study for whom the organization is most efficiently organized.
    1. I wonder what would have happened if someone I trust had provided me with a list of resources and people she admired when I started out in online learning and open education four years ago.

      Interesting scenario. Sounds quite a bit like the role of this one person in grad school who gives you the boost you need. Usually not your director, who’s more of a name than a resource. Possibly someone with a relatively low status. It becomes something of an “informal advisor” role. “Trust” is indeed key, here. My first reaction reading this was to balk at the “trust” part, because critical thinking skills warrant other methods to gather resources. But this is a situation where trust does matter quite a bit. Not that the resources are necessarily better. But there’s much less overhead involved if rapport has been established. In fact, it’s often easy to get through a text or to start a conversation with someone using knowledge of the angle through which they’ve been recommended. “If she told me to talk to so-and-so, chances are that this person won’t take it the wrong way if we start discussing this issue.”

    2. these decisions were ill-informed

      Oh? Pray tell!

    3. if you are still reading these lines

      Thankfully, the TL;DR addressed this at the very top.

    4. curate

      The term may still sound somewhat misleading to those who work in, say, museums (where “curator” is a very specific job title). But the notion behind it is quite important, especially when it comes to Open Education. A big part of the job is to find resources and bring them together for further reuse, remix, and reappropriation. In French, we often talk about «veille technologique», which is basically about watching/monitoring relevant resources, especially online.

    5. Where would you start?
    1. Some people define DH as divided into “hack” -- those who code and make digital things -- and “yack” -- those who critique and analyze “the digital.” I’m also interested in “stack” -- how do the structures of organizations and institutions enable or inhibit what we want to do? The people who “hack” and “yack” can’t work without the people in the “stack” (or without the people in the library stacks).
    1. Imagine if our university system was structured around helping people accomplish the things that they're trying to do, Downes said — "that would be a real transformation."
    1. “We need much more honesty, about what data is being collected and about the inferences that they’re going to make about people. We need to be able to ask the university ‘What do you think you know about me?’”
    2. experts are using learning analytics to try to lower the number of drop-outs
    1. "In a personalized learning environment, a student’s success is defined by knowledge, skills, habits and mindsets," she wrote. "Though we have a lot more work to do, we’re encouraged by student growth and survey results."
    2. much-hyped personalized learning platform

      Emphasis on “hyped”.

  2. Aug 2016
    1. one iteration from success!
    2.  As Neil Selwyn (2013) notes, the expansion of technology (and the rise of EdTech) coincides with a growth in libertarian ideals and neoliberal governmental policies, a one-two punch of individual exceptionalism and belief in the power of the outsider.
    3. EdTech, or really any system or structure permeating society, does not function under modernist sensibilities.
    4. Interestingly, the other MOOC professor at Stanford in 2011, who was not part of the media push or start-up aftermath,  was Jennifer Widom.  She has continued to teach MOOCs since 2011, and during her current sabbatical year is offering free courses in data and design…and those free courses are going to be in-person.

      This puts MOOC hype in perspective, including the Matthew Effect.

    1. play to their strengths while mitigating their weaknesses

      It might be a difficult balancing act and it sounds a bit like the recipe for optimal experience, but it can help situate education models in a more appropriate way.

    2. this model of “personalization” is still building off of a deficit model in which students are steered away from doing the things they are good at so they can focus on the things they are bad at

      Important reminder, cogently stated.

    1. (Apple, Google and Samsung confirm that they don't collect any information about your shopping habits.)
    1. A team at Facebook reviewed thousands of headlines using these criteria, validating each other’s work to identify a large set of clickbait headlines. From there, we built a system that looks at the set of clickbait headlines to determine what phrases are commonly used in clickbait headlines that are not used in other headlines. This is similar to how many email spam filters work.

      Though details are scarce, the very idea that Facebook would tackle this problem with both humans and algorithms is reassuring. The common argument about human filtering is that it doesn’t scale. The common argument about algorithmic filtering is that it requires good signal (though some transhumanists keep saying that things are getting better). So it’s useful to know that Facebook used so hybrid an approach. Of course, even algo-obsessed Google has used human filtering. Or, at least, human judgment to tweak their filtering algorithms. (Can’t remember who was in charge of this. Was a semi-frequent guest on This Week in Google… Update: Matt Cutts) But this very simple “we sat down and carefully identified stuff we think qualifies as clickbait before we fed the algorithm” is refreshingly clear.

    2. appear lower in News Feed.

      Also interesting that they’re not banning it. Probably a good decision. The whole thing sounds a lot with Google’s algorithm update to fight content farms, a few years back.

    3. “He Put Garlic In His Shoes Before Going To Bed And What Happens Next Is Hard To Believe”
    1. The problem, as Taylor explained, is that the rise of e-commerce and social media has lowered the cost of entry for new competitors.

      Sounds like a very quick summary of what Ben Thompson was saying two weeks ago. But, in this case, it’s from “the horse’s mouth”.

  3. Jul 2016
    1. Google’s chief culture officer

      Her name is Stacy Savides Sullivan. She was already Google’s HR director by the time the CCO title was added to her position, in 2006. Somewhat surprising that Sullivan’d disagree with Teller, given her alleged role:

      Part of her job is to protect key parts of Google’s scrappy, open-source cultural core as the company has evolved into a massive multinational.

      And her own description:

      "I work with employees around the world to figure out ways to maintain and enhance and develop our culture and how to keep the core values we had in the very beginning–a flat organization, a lack of hierarchy, a collaborative environment–to keep these as we continue to grow and spread them and filtrate them into our new offices around the world.

      Though “failure bonuses” may sound a bit far-fetched in the abstract, they do fit with most everything else we know about Googloids’ “corporate culture” (and the Silicon Valley Ideology (aka Silicon Valley Narrative), more generally).

    1. One way to do this is to bring someone into the C-Suite whose job it is to keep an eye on culture. The best-known example of this approach is Google GOOG 3.07% , which added “chief culture officer” to head of HR Stacy Sullivan’s job title in 2006. Part of her job is to protect key parts of Google’s scrappy, open-source cultural core as the company has evolved into a massive multinational.

      Interesting that the title would be appended to the HR director position, instead of creating a new position. Stacy Savides Sullivan has been with the Goog’ since 1999, so pretty early in the company’s history. Not sure if her job is specifically with Google or if covers Alphabet more generally. It does sound like Sullivan’s ideas clashed with Astro Teller’s.

    2. Ha! This was before Grant McCracken wrote his famous book!

    1. people mediated by technology in a virtual classroom

      Or people mediated by technology in a face-to-face classroom.

    2. I maintain a great deal of excitement about the potential of the Internet of Things.
    3. heart rate of students as they’re accessing (or not accessing) a course?

      Or brain/electrodermal activity.

    4. what do we do with that information?

      Interestingly enough, a lot of teachers either don’t know that such data might be available or perceive very little value in monitoring learners in such a way. But a lot of this can be negotiated with learners themselves.

    5. How has learning already been changed by the tracking we already do?

      Alfie Kohn probably has a lot to say about this. Already.

    6. By merely being in the room, the devices will monitor students’ behavior in the same way that the cameras and switches and lab coats did in Milgram’s experiments.

      Hope education scientists are deeply concerned about the consequences of their observing learners.

    7. When Internet-enabled devices have thoroughly saturated our educational institutions
    8. Even if I find the experiment itself icky, Milgram offers useful reflections on the bizarre techno theater that made his experiment go.
    9. ensure that students feel more thoroughly policed

      That ship has sailed.

    10. Remote proctoring tools

      Even the NYT got interested, however briefly.

    11. turn students and faculty into data points

      Data=New Oil

    12. E-texts could record how much time is spent in textbook study. All such data could be accessed by the LMS or various other applications for use in analytics for faculty and students.”
    13. But my own personal curiosity and fascination are outweighed by my concern at the degree to which similar devices are being used in education to monitor and police learning.

      Though it’s quite specific, this gap between our personal lives and what we envision in learning contexts underlies a lot of our discussions. It’s almost the opposite of context collapse. Sounds like it’s much more common in formal educational settings than in other contexts for learning.

    14. I’ll be candid. I am quite often an unabashed fan of the Internet of Things.

      Candour may bring us to a new level of dialogue. Sometimes sounds like enthusiasm isn’t allowed, in this scene. Which is a lot of what’s behind the “teaching, not tools” rallying cry. We may be deeply aware of many of the thick, tricky, problematic, thorny issues having to do with tools in our lives. We sure don’t assume that any thing or person or situation is value-free. But we really want to talk about learning. We care about learning. We’re big fans of learning. Cyclical debates about tools are playing in the EdTech court, even when they’re “critical”. Or cynical. Sharing about learning experiences can restore our faith in humanity. Which might be needed after delving so much into the experimental side of social psychology.

    15. relationship cannot be called free of values, ethics, or ideology.

      From Langdon Winner to Symbolic Interactionism.

    16. I find something ominous about the capital-I and capital-T of the acronym IoT
    17. EDUCAUSE Learning Initiative (ELI) report “7 Things You Should Know About the Internet of Things”
    18. And some tools can never be hacked to good use.

      Peremptory.

    19. empty all our LEGOs onto the table

      Apart from the common nitpick (it’s “LEGO blocks”, not “LEGOs”), it’s funny to note how frequently those Danish plastic toys come in pedagogical discussions in the United States. David Wiley even had to belabour another analogy.

    20. ducational technologies have pedagogies hard-coded into them in advance

      Sometimes, this is explicit.

    21. concerned by the idea that our tools are without ideologies
    22. Like Martha
    23. The less we understand our tools, the more we are beholden to them.

      Hence the significance of learning how to code.

    24. the mass of workers are to be blind cogs and pinions in the apparatus they employ
    25. eliciting compliance

      “It’s about teaching, not tools.”

    26. I sense glee in the language Milgram uses
    27. the results remain compelling nonetheless

      At least, they’ve become unavoidable in class discussions even tangentially related to social psychology. In intro sociology, they lead to some interesting thoughts about lab vs. field experiments.

    28. awe

      O RLY?

    29. obedience of volunteers

      A few years ago, the experiment was remade into a tv gameshow. And, according to a documentary on it, was even more effective.

    30. Alexandra “Sasha” Milgram, is played by Winona Ryder, and she serves as the on-screen stand-in for the film audience
    31. The Internet is made of people

      Obligatory Charlton Heston reference. https://www.youtube.com/watch?v=9IKVj4l5GU4

    32. not as a way to monitor and regulate
    33. Internet of Things as a space

      Only partially built up.

    34. reduce students, to mere algorithms
    35. she sees human beings and not the experiment

      “It’s about teaching, not about the experiment.”

    36. and awe

      O RLY?

    37. “counteranthropomorphism”—the tendency we have to remove the humanity of people we can’t see

      Speaking of which… (The byline is particularly interesting given this news item and discussion.)

    1. Unilever is fortunate they don’t have a shaving business to protect

      Was wondering about this and went looking for it. While they do have lots of “personal care” brands (especially deodorants, it sounds like), couldn’t find a shaving business. So, now it makes sense. They’re not disrupting themselves internally by “cannibalising” their own lines. They’re not risking much. They’re not even killing a direct competitor. It even sounds possible that they’re not acq’hiring Levine and Dubin. Most of the Ben piece is about P&G so it’s a bit confusing.

    2. leading to Dollar Shave Club capturing 15% of U.S. cartridge share last year
    1. Both sides are wrong — Yiannopoulos is no free-speech martyr, and cheerleaders of the ban are likely fooling themselves if they interpret this as any sort of sign of evolving Twitter policy rather than a specific instance of damage control that’s unlikely to lead to wider reforms.
    1. (Crooks, 1933; De Zouche, 1945; Kirschenbaum, Simon, & Napier, 1971; Linder, 1940; Marshall, 1968)
    1. “Like the Web” is perhaps a good place to start, don’t get me wrong,
    2. I could have easily chosen a different prepositional phrase. "Convivial Tools in an Age of Big Data.” Or “Convivial Tools in an Age of DRM.” Or “Convivial Tools in an Age of Venture-Funded Education Technology Startups.” Or “Convivial Tools in an Age of Doxxing and Trolls."

      The Others.

    3. “the free software movement does this.” And again, I have to say: not quite. 

      True. But some of us are saying something slightly different. The free software movement shares some of those principles and those go back to a rather specific idea about personal/individual agency.

    4. Convivial tools should be accessible — free, even.

      Free as in (neoliberal) speech.

    5. I’ve heard it suggested often that the World Wide Web is an example of what Ivan Illich called “convivial tools” — although his book predates the Web by 15+ years, Illich speaks of “learning webs” in Deschooling Society. I grow less and less certain that the Web is quite “it."

      Yours in struggle.

    6. the narrative that computer technologies are liberatory
    7. education technology has become about control, surveillance, and data extraction
    8. demanded by education policies — for more data
    9. more efficient (whatever that means)
    10. ed-tech hasn’t really changed much in schools

      Been butting against this quite a bit. One part discouragement: if we haven’t succeed in 40+ years (on the “progressive” side of the spectrum), can we ever succeed? One part nostalgia: education was so radical in the late 1960s and early 1970s. Are we going back to May 1968? Is that what #BlackLivesMatter and the Occupy Movement have been about? One part pseudo-historical: isn’t there a cycle involved, with frequent ups and downs? One part cultural: which contexts are we discussing, here? Is it only about hyperindustrialised societies? Because things sure have changed quite a bit around the world, if not necessarily in the direction we wish they did… One part conceptual: isn’t Ed Tech what we make it to be? Because it sounds like a focus on ed tech solutions, not educational use of technology more generally.

    11. technology industry, the education technology industry programming the child
    12. testing industry programming the child
    13. textbook industry programming the child
    14. The computer isn’t some self-aware agent here, of course.
    15. The computer programming the child.”

      Stallman often uses a similar idea to condemn proprietary software. Rushkoff proposes a similar alternative. Should we choose the red pill or the blue pill?

    16. Much of these new “learn to code” efforts are about inserting computer science into the pre-existing school curriculum.
    17. create their own interactive learning tools
    18. For all media, the original intent was 'symmetric authoring and consuming’.”

      Sounds like the original television.

    19. qualitatively extend the notions of 'reading, writing, sharing, publishing, etc. of ideas' literacy to include the 'computer reading, writing, sharing, publishing of ideas
    20. reflexive communication

      Just a couple of years ago, Noam Chomsky finally understood that this is a large part of what we do with language. A significant proportion of language sciences has been assigned to getting him to get this. It took 40 years.

    21. children would be the primary actors in this transformation
    22. He believed this would foster a new literacy, a literacy that would bring about a revolution akin to the changes brought about by the printing press in the 16th and 17th centuries.
    23. Alan Kay
    24. a way for children could to learn computer programming but more importantly even, a way of giving them a powerful object, a powerful tool to think with

      There’s a lot of ambivalence about recent projects which seek to involve coding in a broader educational context. There’s probably a lot of backlash to come against the STEM focus of many of these programs. At the same time, though, coding has become the de facto power tool in “our world”, for better or worse. Which is part of the reason it’s so interesting to trace, as Fred Turner famously did, the roots of “cyberculture” in the 1960s “counterculture”. In both cases, the “culture” part is rooted in a certain part of the United States which links two Bays (San Francisco and Massachusetts). Even the discourse on empowerment is part neoliberal, part anti-establishment.

    25. more in common with multiple choice than with student choice and agency

      Nice wording.

    26. progressive change

      Which isn’t that clear from an outside perspective. It often sounds a bit like some form of Left-leaning perspective, in a French tradition («La Gauche»), but it’s also predicated on a fairly neoliberal notion of progress.

    27. school often neatly reinforces the hierarchies of our socio-economic world

      Though it came out a few years after the texts listed in the previous paragraph, Randall Collins’s Credential Society would be relevant.

    28. our education system is controlling, exploitative, imperialist
    29. education technologies that are not build upon control and surveillance
    30. whose revolution this might be
    31. resist some of the dominant narratives about what education technology can or should do

      Yours in struggle.

    32. should probably not send my readers into this downward spiral of education technology despair

      Too late?

    33. You hone your jokes; perhaps you localize them

      Ha! Speaking of localisation…

    34. don’t give ed-tech pep talks, where you leave the room with a list of 300 new apps you can use in your classroom.

      The impact these talks have is difficult to assess. Some may be quick to blame people for attending such talks. But it’s hard to fight cheery, enthusiastic pronouncements when your job is devalued.

    35. (Let me stress “gender” there. I can’t but notice that this list, much like the list of those on the education speaking circuit today, is full of men.) 
    36. The phrase comes from his 1973 book Tools for Conviviality, published just 2 years after the book he’s probably best known for, Deschooling Society.  These are just two of a number of very interesting, progressive if not radical texts about education from roughly the same period: Paul Goodman’s Compulsory Mis-education (1964). Jonathan Kozol’s Death at an Early Age (1967). Neil Postman’s Teaching as a Subversive Activity (1969). Paulo Freire’s Pedagogy of the Oppressed (first published in Portuguese in 1968 and in English in 1970). Everett Reimer’s School is Dead (1971).
    1. series of radical educational paperbacks, published by Penguin in the series Penguin Education Specials in the 1970’s. These included: Paulo Freire Pedagogy of the Opprressed ; Paul Goodman Compulsory Miseducation; Ivan Illich De-Schooling Society; Everett Reimer School is Dead. 
    1. cautiously optimistic

      One of the many reasons we need Maha in our world. Honestly, there’s a lot out there to bring us down. The problem with that, in part, is that it may discourage the most courageous among us. Not Maha, though. Proving once again how courageous she is (despite her claim to the contrary), she brings us forward on our quest for empowered learning despite technology.

    2. data being collected about individuals for purposes unknown to these individuals
    3. This means that even the ‘free choice’ of finding your own content and communicating with others is not completely in your own hands as a learner.
    4. There is a lot of power coming from organisations that choose to fund particular initiatives and institutions who are able to push their content onto the rest of the world.

      On one hand, we might hope that there’ll be a shift in power and that these choices will eventually benefit those who are currently underprivileged. In that reading, this “backstep” is maybe more of a system feature. On the other hand, it can be perceived as being in line with the notion that philanthropy contributes to wealth inequality. In this context, much of the good intentions behind MOOCs can be assessed in a new light.

    5. There is still much more emphasis in hyperbolic education discourse on pushing content rather than enabling connections between people

      There is. But it might be shifting a bit. Or, at least, there are people around who are proposing another Sphere of Agency, one which relies much less on content and does a lot more with openness. As with Berkana, our job might be to connect these people who sing in a different voice. We might reach richer harmonies when we don’t expect unison.

    6. I don’t want to dwell on all the things that are still going wrong

      Maha does a neat job of bringing in diverse points, from postive to negative, neutral to orthogonal. But it’s very difficult, in this scene, to maintain our enthusiasm. Put another way, it’s incredibly easy to become cynical. Part of it may just be the academic mode of thought. We can’t enjoy something without criticising it at the same time. Another part may be the very polarised contexts in which many members of the scene live. There’s a lot of anger in some parts of the World. An effect of this, though, is the contrast with the cheery enthusiastic starry-eyed optimism of technocentric EdTech solutionist solution vendors (aka, “The Other Side”). If you have gloomy people on one end of the spectrum and feel-good sales reps on the other, it’s not necessarily that surprising that some teachers spend more time checking out “the top ten apps which will make your teaching a joyful pleasurable experience which really does empower those kids, we promise you and you can trust us because we’re good people”.

    7. those less privileged in developed countries

      Getting intersectional?

    8. academics in developing countries
    9. not to conference content, but to up-to-date conversations in the education field

      Lots of (welcome) “product/process” talk during #DigPed PEI.

    10. localised to different regional contexts and curricula

      Local appropriation could lead to something interesting. Typically, though, localisation is a top-down process: take a culture-specific item, strip it down to its bare essentials, make it available in other cultural contexts, add a bit of local flavour.

    11. efforts to expand worldwide

      At the risk of sounding cynical (which is a very real thing with annotations), reaching a global market can be very imperialistic a move, regardless of who makes it.

    12. encouraged learners to use social media

      To me, the key part here is “encouraged”, as opposed to “forced” or even “asked”. Imposed solutions are neocolonial. There can be a lot of postcolonial reappropriation of existing tools.

    13. Some digital pedagogues who teach MOOCs on traditionally xMOOC platforms find ways to infuse connectivist principles in their teaching.
    14. content can potentially come from outside the developed world

      Which might help. It could also force unwarranted comparisons.

    15. on already-existing MOOC platforms like Coursera
    16. Towards a More Postcolonial Internet for Learning

      A postcolonial Internet, yes. Especially if we revisit the current one’s history. But the piece is mostly about postcolonial MOOCs and that’s much more specific.

    17. many people in the world without internet access, or with insufficient infrastructure
    18. Translation apps continue to leave much to be desired.

      Cue Roman Jakobson. In a way, by giving the illusion of mutual understanding, these apps exacerbate the problem. Also, because they do the worst job with rich language work (nuance, subtlety, wordplay, polysemy, subtext…) they encourage a very “sterile” language which might have pleased Orwell like it pleases transhumanists, but which waters down what makes language worth speaking.

    19. what is the English-speaking world missing out on by not reading the content written in other languages

      Though he’s been associated with a very strange idea he never had, Edward Sapir was quite explicit about this loss over a hundred years ago. Thinking specifically about a later passage warning people about the glossocide English language. But it’s been clear in his work from long before that excerpt that we’re missing out when we focus on a single language.

    20. people who are not fluent in English

      In this case, it can apply to quite a few academics who are native speakers of one of the aforementioned “world languages”. Difficult to be a monolingual academic in an exclusively local language. Much easier as a French- or Mandarin-speaker to become an academic without learning much English. And speaking of monolinguals, there is a clear bias in tech towards monolingualism.

    21. the voice of the rest of the world
    22. a handful in a few major world languages

      One might think that those other languages are well-represented. People connected with the Open Knowledge Foundation are currently tackling this very issue. Here, Open Education isn’t just about content.

    23. ironically while continuing to employ adjunct faculty

      Much hiding in this passing comment. As adjuncts, our contributions to the system are perceived through the exploitation lens.

    24. privileged institutions
    25. The majority of content comes from Western, developed countries
    26. expand access to some knowledge
    27. afford a university education