1154 Matching Annotations
  1. Feb 2017
  2. Dec 2016
    1. Given all of this, it might only be a matter of time before watchmaker Fossil (FOSL) takes a write-down on its $260 million 2015 purchase of wearables firm Misfit. And unless its non-smartwatch products prove very successful, Nokia  (NOK) might struggle to make its $191 million spring acquisition of French wearables/fitness hardware maker Withings pay off.

  3. Nov 2016
    1. make the things that you want to see in the world

      Much more appropriate than the apocryphal Gandhi quote.

    1. Best piece I’ve seen on last week’s announcements.

      Gruber had linked to Michael Tsai’s roundup of the backlash, calling it “must-read stuff”. In this case, though, Gruber is “throwing his hat in the ring”. And the ring now feels like the site of a burgeoning flamewar. Issue is, here, that the “war” is happening about people who actually enjoy Apple’s products. This isn’t the “religious wars” between Macs and PCs or between Fandroids and Apple fanbois. It’s a whole argument between people who have been purchasing Apple computers and wanted updated ones. A well-known lesson from social psychology is that group polarization deepens divides by encouraging extreme positions. Chuq Von Rospach’s piece contains several comments which could be qualified as “extreme”. And it puts the blame on those who disagree. There are similar pieces on the other side of the equation, surely. Tsai’s roundup should make it possible to identify them. But Gruber has yet to link to them (apart from arguing about specific points like Tim Cook’s quote on the irrelevance of “PCs” and trying to set the record straight on Apple and Intel sharing responsibility for the 16GB limits on new top-of-the-line MacBook Pro desktop replacements).

      As an example of the effect of group polarization: my own perspective is that disappointment is real. Wasn’t impressed by what transpired from last week’s announcement. Feeling a bit more excited about the Microsoft Surface Studio than about the Touch Bar, but will likely not buy either any time soon. Because polarization forces me to take sides, my vote would go for the “there’s a serious problem, here”. Not saying Apple is doomed or that each of the problems discussed is a tragedy. But, to me, what is being thrown around sounds quite reasonable, not “trivial and petty”. Can’t be on Von Rospach’s side if that’s where the line is drawn. “You’re either with us or against us.” If you force me to choose, well, bye bye!

    1. uncertainty is bad news for the user base

      People are reacting to this uncertainty. Trying to prove them wrong achieves polarization instead of insight.

  4. Oct 2016
    1. most importantly, the co-worker is not white.

      Well… Is that the most important thing? Is it so unproblematic?

    2. The best way to attract and grow an audience for political content on the world’s biggest social network is to eschew factual reporting and instead play to partisan biases using false or misleading information that simply tells people what they want to hear.

    1. That's why BI Intelligence has spent months creating the most exhaustive resource on not just education, but the entire IoT: The Internet of Things: Examining How The IoT Will Affect The World.

    2. But education is far from the only area of our lives that the IoT will transform. Transportation, energy, homes, healthcare, and more will all feel the touch of the IoT in the coming years.

    3. With figures like those, it's clear that the education system isn't going away anytime soon.

      How so?

    4. company sinking its hooks into the U.S. school system

      Interesting choice of words.

    5. SMART boards changed the way teachers and students interacted in the classroom by moving lessons away from the dusty chalkboards that dominated education for decades.

    6. Capterra notes that an average school spends an average of $30,000 to $50,000 per year just on paper, but reusable tech would completely eliminate that cost.

    7. Outside of the classroom, universities can use connected devices to monitor their students, staff, and resources and equipment at a reduced operating cost, which saves everyone money.

    8. Devices connected to the cloud allow professors to gather data on their students and then determine which ones need the most individual attention and care.

    1. Other smartwatches force you into nightly charging.

      Honestly, this has been a major point for me not to go with Apple Watch (even before knowing about the Pebble 2+ Heart Rate). Such small things but smart alarms and sleep tracking really do help me quite a bit.

    1. recording of a phone call from Apple (without their consent, which is illegal in California, but apparently not in Romania).

      The legality of recording phone conversations in Romania takes special meaning in historical context.

    1. Trump had less “fleeting interjections” this debate than the first round, and slightly more interruptions. Clinton had slightly less fleeting interjections, and the same amount of interruptions. The moderators, however, were much more active in this debate than in the first. They interjected (usually to let the candidate know they were running out of time) 41 times throughout the 90 minute debate.

    2. In 2015, 24 percent of the oil we used was imported, but we get more of that from Canada than from all the OPEC countries combined.

    3. The president is not a prime minister — it’s an individual making decisions, sitting atop an entire branch of government.

      So, Prime Ministers don’t make decisions, sitting atop an entire branch of government?

    4. (I’m not condoning the stigmatization of mental illness, btw.)

      Phew!

    1. In the end, your assessment of Trump’s chances comes down to the same consideration as with a falling stock: How sound are the fundamentals? Is Trump the equivalent of a beleaguered blue-chip that still has lots of hard assets?

  5. remikalir.com remikalir.com
    1. (Holden, 2016a; Kalir, forthcoming)

      Might be a good time to ask about the name change. Hope it’s not too indiscreet.

    1. For G Suite users in primary/secondary (K-12) schools, Google does not use any user personal information (or any information associated with a Google Account) to target ads.

      In other words, Google does use everyone’s information (Data as New Oil) and can use such things to target ads in Higher Education.

    1. You can’t say the Nexus phones don’t count just because they never succeeded.

      No, but you can say they don’t count because they were made by other manufacturers. They were Google-branded and had some Google-specific features (or, at least, lack of bloatware). But they weren’t Google’s handsets.

    2. Google has been going head-to-head against the iPhone ever since the first Android phone debuted.

      Sure. At least, Android has. But the idea is that these are Google’s first handsets.

    1. How does the heart rate monitor work? The Pebble 2 and Time 2 will use optical heart rate monitors that will monitor heart rate constantly during a workout.  When at rest or sleeping, heart rate will be monitored every 10 minutes, ensuring your resting heart rate is monitored with little to no battery life impact. The monitor will have no problem with sweat, but won’t provide heart rate readings when submerged in water. Please note:  Pebble devices with a heart rate (HR) monitor are intended to be a valuable tool that can provide an accurate estimation of the user’s heart rate. Pebble smartwatches are not medical devices and you should not rely on the accuracy of heart rate data for any purpose, especially for medical or health purposes.

      Straight from the horse’s mouth. We now know that heart rate monitoring on the Pebble smartwatches is as infrequent as the Apple Watch. Ah, well… What remains to be known is what “constantly” means, for workouts. Every second, as with Fitbit?

    1. Once you pay for 12 full MiWay fares during any one-week (Monday to Sunday) using your PRESTO card, you can then ride free on MiWay for the remainder of that week!

      Those loyalty programs are pretty interesting. Wish the same existed for day and monthly passes.

    1. Were he to become president, his casual remarks — such as saying he wouldn’t defend NATO partners from invasion — could have devastating consequences.Trump has praised Russian President Vladimir Putin, a thug who has made it clear he wants to expand Russia’s international footprint.Trump suggested Russia engage in espionage against Hillary Clinton — an outrageous statement that he later insisted was meant in jest.

      The Cold War isn’t over.

    2. SB 1070, the 2010 “show me your papers” law that earned Arizona international condemnation and did nothing to resolve real problems with undocumented immigration.

      Public opinion matters.

    3. Endorsement: Hillary Clinton is the only choice to move America ahead

      Hillary Clinton: Not a Loose Cannon Shooting Verbal Spit Wads.

    1. USA TODAY's Editorial Board: Trump is 'unfit for the presidency'

      Strong (written) language. In the video, the paralanguage makes things sounds quite a bit more difficult. Fear of reprisals? Unwilling shift to clickbait?

  6. Sep 2016
    1. In terms of hardware, before Apple Watch debuted in 2014, there were a lot of rumors about the wearable including a multitude of health sensors that could track things like blood glucose or blood oxygen.

      A lot of these rumours appeared on 9to5mac, of course…

    1. (Crazy app uptake + riding data + math wizardry = many surprises in store.)

      Like Waze for public transit? Way to merge official Open Data from municipal authorities with the power of crowdsourcing mass transportation.

    1. heart disease, diabetes and cancer

      Not the best source or argumentation. But these are the key ones we may remember from Eaton, Konner, and Shostack

    1. Facebook Twitter LinkedIn GooglePlus jQuery(document).ready(function() { "use strict"; $ = jQuery; var decal = $('.c-socialbar-cta:not(.horizontal)').parent().width(); $('.c-socialbar-cta:not(.horizontal)').css({'margin-left':decal+5}); $('.c-socialbar-cta:not(.horizontal)').fadeIn(); $(window).scroll(function() { socialbar.scroll(); }); }); var socialbar = (function(jQuery) { var timeOutId = 0; var jitterBuffer = 20; return { scroll:function() { var offset = $('.c-socialbar-cta:not(.horizontal)').parent().offset(); var top = offset.top -150; //alert(offset.top); if ($(window).scrollTop() > top) { $('.c-socialbar-cta:not(.horizontal)').addClass('fixed'); } else { $('.c-socialbar-cta:not(.horizontal)').removeClass('fixed'); } } }; })(); Message from the president: 'This is a victory for academic freedom'

    1. "The university is thankful that the tireless efforts of governments, diplomats and colleagues across Canada and internationally were successful. The Concordia community — in particular faculty and staff members and unions — played a critical role in securing her release. This is a victory for academic freedom."

    1. As many universities are being queried by the federal government on how they spend their endowment money, and enrollment decreases among all institutions nationally, traditional campuses will need to look at these partnerships as a sign of where education is likely going in the future, and what the federal government may be willing to finance with its student loan programs going ahead.

      To me, the most interesting about this program is that it sounds like it’s targeting post-secondary institutions. There are multiple programs to “teach kids to code”. Compulsory education (primary and secondary) can provide a great context for these, in part because the type of learning involved is so broad and pedagogical skills are so recognized. In post-secondary contexts, however, there’s a strong tendency to limit coding to very specific contexts, including Computer Science or individual programs. We probably take for granted that people who need broad coding skills can develop them outside of their college and university programs. In a way, this isn’t that surprising if we’re to compare coding to very basic skills, like typing. Though there are probably many universities and colleges where students can get trained in typing, it’s very separate from the curriculum. It might be “college prep”, but it’s not really a college prerequisite. And there isn’t that much support in post-secondary education. Of course, there are many programs, in any discipline, giving a lot of weight to coding skills. For instance, learners in Digital Humanities probably hone in their ability to code, at some point in their career. And it’s probably hard for most digital arts programs to avoid at least some training in programming languages. It’s just that these “general” programs in coding tend to focus almost exclusively on so-called “K–12 Education”. That this program focuses on diversity is also interesting. Not surprising, as many such initiatives have to do with inequalities, real or perceived. But it might be where something so general can have an impact in Higher Education. It’s also interesting to notice that there isn’t much in terms of branding or otherwise which explicitly connects this initiative with colleges and universities. Pictures on the site show (diverse) adults, presumably registered students at universities and colleges where “education partners” are to be found. But it sounds like the idea of a “school” is purposefully left quite broad or even ambiguous. Of course, these programs might also benefit adult learners who aren’t registered at a formal institution of higher learning. Which would make it closer to “para-educational” programs. In fact, there might something of a lesson for the future of universities and colleges.

    2. As many universities are being queried by the federal government on how they spend their endowment money, and enrollment decreases among all institutions nationally, traditional campuses will need to look at these partnerships as a sign of where education is likely going in the future, and what the federal government may be willing to finance with its student loan programs going ahead.

      To me, the most interesting about this program is that it sounds like it’s targeting post-secondary institutions. There are multiple programs to “teach kids to code”. Compulsory education (primary and secondary) can provide a great context for these, in part because the type of learning involved is so broad and pedagogical skills are so recognized. In post-secondary contexts, however, there’s a strong tendency to limit coding to very specific contexts, including Computer Science or individual programs. We probably take for granted that people who need broad coding skills can develop them outside of their college and university programs. In a way, this isn’t that surprising if we’re to compare coding to very basic skills, like typing. Though there are probably many universities and colleges where students can get trained in typing, it’s very separate from the curriculum. It might be “college prep”, but it’s not really a college prerequisite. And there isn’t that much support in post-secondary education. Of course, there are many programs, in any discipline, giving a lot of weight to coding skills. For instance, learners in Digital Humanities probably hone in their ability to code, at some point in their career. And it’s probably hard for most digital arts programs to avoid at least some training in programming languages. It’s just that these “general” programs in coding tend to focus almost exclusively on so-called “K–12 Education”. That this program focuses on diversity is also interesting. Not surprising, as many such initiatives have to do with inequalities, real or perceived. But it might be where something so general can have an impact in Higher Education. It’s also interesting to notice that there isn’t much in terms of branding or otherwise which explicitly connects this initiative with colleges and universities. Pictures on the site show (diverse) adults, presumably registered students at universities and colleges where “education partners” are to be found. But it sounds like the idea of a “school” is purposefully left quite broad or even ambiguous. Of course, these programs might also benefit adult learners who aren’t registered at a formal institution of higher learning. Which would make it closer to “para-educational” programs. In fact, there might something of a lesson for the future of universities and colleges.

    1. The Future of the Professions: How Technology Will Transform the Work of Human Experts

    2. associate professor of economics at the University of British Columbia and a faculty research fellow at the National Bureau of Economic Research

      Somewhat surprising that (apparently US-based) NBER would have involvement from a professor at a Canadian university. Typically, those “national bureaus” focus on “nationals”.

    3. “The Future of Employment: How Susceptible Are Jobs to Computerisation?”

    4. Machines are learning to do things that once could only be done by humans, and I see no obvious endpoint to their progress.

    5. learn how to access information

    6. Only Humans Need Apply: Winners and Loser in the Age of Smart Machines

    7. which skills they’d focus on if they were about to start their first year of college this fall

    8. It is by now close to certain that there are millions of people currently in high school and college who are fine-tuning their skills for steady-looking careers that will, following technological breakthroughs, dissipate by the time they retire.

    1. Take-Two Interactive Software, Inc., 2K and Firaxis Games Partner with GlassLab Inc., to Bring CivilizationEDU to High Schools Throughout North America in 2017

    1. Finally, in order for data-driven interventions to be wide-spread, institutions must sustain a culture that embraces the use of data, and create incentives for data-driven activities amongst administrators, instructors and student support staff. Large-scale, data-driven policy changes are implemented with minimal friction and maximal buy-in when leaders demonstrate a commitment to data-informed decision-making, and create multiple opportunities for stakeholders to make sense of and contribute to the direction of the change. Users not only need to be trained on the proper ways to use these tools and communicate with students, they also require meaningful incentives to take on the potentially steep learning curve.[40]

      Thankfully, this paragraph isn’t framed as a need for (top-down) “culture change”, as is often the case in similar discussions. Supporting a culture is a radically different thing from forcing a change. To my mind, it’s way more likely to succeed (and, clearly, it’s much more empowering). But “decision-makers” may also interpret active support as weaker than the kind of implementation they know. It’s probably a case where a “Chief Culture Officer” can have a key role, in helping others expand their understanding of how culture works. Step 1 is acknowledging that culture change isn’t like a stepwise program.

    2. Users not only need to be trained on the proper ways to use these tools and communicate with students, they also require meaningful incentives to take on the potentially steep learning curve.[40]

    3. Application Modern higher education institutions have unprecedentedly large and detailed collections of data about their students, and are growing increasingly sophisticated in their ability to merge datasets from diverse sources. As a result, institutions have great opportunities to analyze and intervene on student performance and student learning. While there are many potential applications of student data analysis in the institutional context, we focus here on four approaches that cover a broad range of the most common activities: data-based enrollment management, admissions, and financial aid decisions; analytics to inform broad-based program or policy changes related to retention; early-alert systems focused on successful degree completion; and adaptive courseware.

      Perhaps even more than other sections, this one recalls the trope:

      The difference probably comes from the impact of (institutional) “application”.

    4. the risk of re-identification increases by virtue of having more data points on students from multiple contexts

      Very important to keep in mind. Not only do we realise that re-identification is a risk, but this risk is exacerbated by the increase in “triangulation”. Hence some discussions about Differential Privacy.

    5. the automatic collection of students’ data through interactions with educational technologies as a part of their established and expected learning experiences raises new questions about the timing and content of student consent that were not relevant when such data collection required special procedures that extended beyond students’ regular educational experiences of students

      Useful reminder. Sounds a bit like “now that we have easier access to data, we have to be particularly careful”. Probably not the first reflex of most researchers before they start sending forms to their IRBs. Important for this to be explicitly designated as a concern, in IRBs.

    6. Responsible Use

      Again, this is probably a more felicitous wording than “privacy protection”. Sure, it takes as a given that some use of data is desirable. And the preceding section makes it sound like Learning Analytics advocates mostly need ammun… arguments to push their agenda. Still, the notion that we want to advocate for responsible use is more likely to find common ground than this notion that there’s a “data faucet” that should be switched on or off depending on certain stakeholders’ needs. After all, there exists a set of data use practices which are either uncontroversial or, at least, accepted as “par for the course” (no pun intended). For instance, we probably all assume that a registrar should receive the grade data needed to grant degrees and we understand that such data would come from other sources (say, a learning management system or a student information system).

    7. Data sharing over open-source platforms can create ambiguous rules about data ownership and publication authorship, or raise concerns about data misuse by others, thus discouraging liberal sharing of data.

      Surprising mention of “open-source platforms”, here. Doesn’t sound like these issues are absent from proprietary platforms. Maybe they mean non-institutional platforms (say, social media), where these issues are really pressing. But the wording is quite strange if that is the case.

    8. 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.

    9. 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.

    10. 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. Steven Mintz is Executive Director of the University of Texas System's Institute for Transformational Learning and Professor of History at the University of Texas at Austin.

      Sounds like MOOCs have been part of his role, at least in UT’s collaboration with edX. Which brings an interesting context to the piece, especially in view of what we might call “the end of the MOOC moment”.

    2. commenting

      From one of the Disqus comments:

      Which piece did you read?

      Though seemingly innocuous, this comment gets much closer to an ad hominem attack than to a throughtful conversation. The rest of the comment is ok, but it’s with slips like these that we get into flamewars.

    3. One of postmodernism’s key insights is that many practices that seem natural or inevitable are anything but. 

      Somewhat unexpected nod to critiques of essentialism. Makes sense in context.

    4. Faculty, in such contexts, demonstrate skills less apparent in conventional classroom environments. In team-based courses, faculty must serve as learning architects, mentors, and instructional scaffolders, as well as content experts and providers of feedback and evaluation.

    5. Formalized course sharing and cross-registration arrangements

      There are examples of this in Ontario. But such arrangements require a significant shift in the way people conceive of enrollment.

    6. We might also blur the lines separating the campus from the outside world, by integrating more experiential learning into educational pathways, whether in the form of internships or e-internships, clinical or field experiences, or service learning, and further blur the line between high school and post-secondary education by integrating foundational courses, tightly aligned with college expectations, into secondary school.

      A fair amount to unpack, here. But it sounds like the core idea of the piece relate to “The Great Unbundling of Education”, with nods to informal learning and cross-sector training.

    7. All of us recognize that students’ communication skills benefit greatly from substantial amounts of writing. But many faculty members limit the amount of assigned writing because drafting comments and grading is too time-consuming. But one can imagine other ways to give students more opportunities to write while ensuring that they receive valuable feedback. These might include peer or near peer feedback, using carefully designed rubrics, or even a degree of auto feedback.

    8. Many of the roughly forty percent of students at four-year institutions who never graduate would benefit greatly from access to alternate credentials.

    9. 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. 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”.

  7. 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”.

  8. 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!