1200 Matching Annotations
  1. Sep 2017
    1. the LMS is the minivan of education. Everyone has them and needs them, but there’s a certain shame having one in the driveway.

    1. The manager then starts writing a request for proposals. This process often starts with an email asking other campus-technology officers to share their own versions. After getting three or four of them, sometimes from wildly different types of colleges with wildly different needs, the manager may start cutting and pasting together bits from the various documents. There is a lot of pasting, but not so much cutting. Lists of requirements are added together, and then added to based on whatever the selection committee comes up with.

    2. Learning-management systems, like any product, evolve because of a kind of natural selection — or unnatural selection, in this case.

    1. Tsugi is a multi-tenant scalable LTI library and tool hosting environment. It is intended to make it more tractable to implement the Application Store that we will need for the Next Generation Digital Learning Environment.

    1. A Flexible, Interoperable Digital Learning Platform: Are We There Yet? Posted on May 28, 2017 Categories:Ed Tech, Interoperability, Learning Apps, LMS & Learning Platforms Tags:IMS, IMS Caliper, Learning Platform, LMOS, LTI, NGDLE By Michael FeldsteinIn 2005, some colleagues and I had been tasked with identifying a single LMS that could serve the needs of all 64 campuses of the State University of New York—from Adirondack Community College to SUNY Stony Brook to the two medical schools. We came to the conclusion that no single LMS at the time could meet such diverse needs. We proposed instead that SUNY should build a modular system from which each campus, and indeed each educator, could create their own fit-for-purpose digital learning environment. We called this idea the Learning Management Operating System, or LMOS.

    1. Next Generation Digital Learning Environment (NGDLE) As mentioned in the Medium blog, the setup for the commons was described as going in the direction described by the EDUCAUSE NGDLE report. One thing North Carolina is doing is turning the typical LMS-driven procurement approach on its head. When I asked Rascoff how the apps would be pulled together, he said that the primary plan was to set up all accepted apps with Single Sign On (SSO) capabilities. Rascoff described that since the LMS is not where learning occurs for the most part, his team is leaving that decision up to the campuses and focusing their efforts on the learning apps.

    1. Just about every school in the US and Canada, and many across the world, has an LMS, and every LMS has a grade book. While the degree to which faculty utilize it varies greatly, it is typically one of the most utilized tools, at least for the basic purposes of communicating grades to students and the registrar. In fact, many schools require faculty to enter grades in the LMS grade book.

    1. In the mid-1990s, largely unaware of Bloom's challenge, innovative faculty members and students at universities throughout the world began thinking about ways to leverage the Internet and the World Wide Web to improve teaching and learning. The result was the creation of a new category of web-based software: the "course management system" or CMS. Alternatively labeled learning management systems (LMSs), learning content management systems (LCMSs), and virtual learning environments (VLEs), such software has generally been focused primarily on helping teachers increase the efficiency of the administrative tasks of instruction (e.g., distribute documents, make assignments, give quizzes, initiate discussion boards, assign students to working groups, etc.). This instructor-centrism comes despite the best intentions and efforts of system designers, early adopters, and instructional support staff who sought to use these systems to transform the dominant learning modality of higher education from traditional, classroom-based instruction to online and hybrid courses. In practice, the vast majority of instructors who adopted the CMS largely ignored Bloom's challenge to make an "educational contribution of the greatest magnitude," instead focusing on increasing the administrative efficiency of their jobs.

    1. Learning paths allow you to assemble two or more courses into a path that students must complete to trigger completion actions.

    2. I think a lot of faculty are still at the point where they need a stack of papers and red pen.

      Emphasis on “still”. Direction of change?

    1. Learning Analytics researchers have long held that the contexts of learning are critical in making meaningful analyses. With the large data footprint that Blackboard has to analyze, our team is able to look at some of these contexts in depth.

    1. Could different co-teaching and collaborative course approaches or more modern pedagogical practices move the needle more than the latest LMS features? 

    2. LMSs limit the visibility of copyrighted course content to only course participants for the duration that they need it. (Of course, this would become a moot point if using openly licensed OERs.)

    3. Over the course of many years, every school has refined and perfected the connections LMSs have into a wide variety of other campus systems including authentication systems, identity management systems, student information systems, assessment-related learning tools, library systems, digital textbook systems, and other content repositories. APIs and standards have decreased the complexity of supporting these connections, and over time it has become easier and more common to connect LMSs to – in some cases – several dozen or more other systems. This level of integration gives LMSs much more utility than they have out of the box – and also more “stickiness” that causes them to become harder to move away from. For LMS alternatives, achieving this same level of connectedness, particularly considering how brittle these connections can sometimes become over time, is a very difficult thing to achieve.

    1. This implies to me that an even greater cultural change is needed around what it means to be a student than a teacher.

    2. A framework that allows individuals to innovate easily, in a sharable way, without needing permission.

  2. Aug 2017
    1. introduce topic modeling to those not yet fully converted aware of its potential.

      Is resistance futile?

    2. They’re powerful, widely applicable, easy to use, and difficult to understand — a dangerous combination.

  3. mimno.infosci.cornell.edu mimno.infosci.cornell.edu
    1. Using other people's code is an important part of programming, but for group projects the code should be substantially the work of the group members except for standard libraries.

    2. LaptopsIn order to facilitate interactive in-class work, you are allowed to bring a laptop.

    3. "Multitasking" is a myth.

    4. If you have a laptop, you will be expected to use it for relevant work.

    5. Work in pairs will be encouraged.

    6. A typical week

    1. In writing the description of our reverse engineering work below, we deliberately avoid terms that are commonly used in Machine Learning, where labels are "true," "correct," or "gold standard." This linguistic distinction highlights the fundamentally different perspective that humanists have on classification as a tool. Our goal is not to create a system that mimics the decisions of a human annotator, but rather to better represent the porous boundaries between labels and identify the piles on which a story could have been placed over a century ago late on a cold wintry night in a dimly lit schoolhouse in eastern Jutland. We note the contrast between our use of computers to problematize existing distinctions and the common concern in the Humanities that computers deal only with binaries and black-and-white distinctions.

      Valuable insight and eloquently phrased.

    2. Our goal is not to treat existing classifications as "ground truth" labels and build machine learning tools to mimic them, but rather to use computation to better quantify the variability and uncertainty of those classifications.

    3. Our goal with this classification method can be seen as the inverse of usual machine learning classifiers.

    1. Analytics for Learn allows the analysis of teachers’ performance as well, something that will prove controversial in many institutions but will be increasingly of interest to senior managers who wish to monitor the quality of teaching in ways that were never possible in traditional classroom settings.

    1. Bottom-up mining of patterns may reveal phenomena that nobody was predicting based on formal theory, and to which we are therefore blinded. It will be an exciting moment when an unexpected pattern in the data, discovered by an algorithm as an apparent anomaly, leads to a theoretical breakthrough.

    1. Be the skunk at the party. Because it’s intelligent skunks, not cheerleaders, that this field needs right now.

    1. learning analytics are processes or procedures used to analyze student data to algorithmically predict outcomes, intervene in the learning process, and uncover patterns of learning behavior

    1. This has much in common with a customer relationship management system and facilitates the workflow around interventions as well as various visualisations.  It’s unclear how the at risk metric is calculated but a more sophisticated predictive analytics engine might help in this regard.

      Have yet to notice much discussion of the relationships between SIS (Student Information Systems), CRM (Customer Relationship Management), ERP (Enterprise Resource Planning), and LMS (Learning Management Systems).

    1. watching videos of people making claims that seem odd and then executing some Google searches to see if primary materials support the claims made by smug TED lecturers

      Sounds like an exercise for a course.

    1. The most obvious pathway is the stepping stones aproach. Sequential in nature, it involves doing one step at a time in a prescriptive manner. See for example, Doug Belshaw’s kanban badges using Trello. Another option is where badges are a part of a collection. Like the game Trivial Pursuit, this is where several achievements are grouped together in a non-linear manner. Perscriptive in nature, collections can be linked with the completion of standards or levelling up. In contrast to perspective badge ecosystems, constellations offer a more open-ended approach where users can choose from a range of possibilities, carving out any number of pathways. This is conducive to life-long learning and offers the potential to write your own learning story. Open to borrowing from different providers, it is for this reason that it is descriptive rather than prescriptive.

  4. Jul 2017
    1. What is important about learning pathways, is that any individual can learn what they want, when they want, how they want. In professional development and conference planning, we would talk about a common assured/shared experience. Basically, what is the one thing that someone will definitely get from this their time with us. Learning pathways takes this a step further and tries to document how and what you should learn. The purpose is that a learner might want to some guidance on what this all means, but not want a scripted curriculum.

  5. Jun 2017
    1. Anyone working with the latest generation of MIDI musical instruments – like the Eigenharp, LinnStrument, ROLI Seaboard, Haken Continuum and the Madrona Soundplane – has probably encountered the work of Belgium-based programmer & electronic musician Geert Bevin.

      My thoughts exactly.

      And it carries over to much of the world of expressiveness in electronic music, centred around the emerging MPE standard: Multidimensional Polyphonic Expression.

      Let me geek out a minute. ;)

      Coming late to this MPE game, been really taken by the fact that Bevin’s name is everywhere. Given his work with many manufacturers, it’s no exaggeration to say that this type of musical expressiveness wouldn’t have expanded the way it did if it weren’t for Geert Bevin. Of course, MPE isn’t that mainstream, yet. You could even say that it’s a bit of a niche, in terms of the already peculiar world of electronic music. Besides, it’s just an implementation of some things which have been in the MIDI specifications from the start, over 30 years ago. But there’s more than smoke, here.

      A few days ago, ROLI has announced the Seaboard Block, which might be the most affordable MPE device as of yet. It’s also the missing piece of the puzzle in ROLI’s lineup, linking the Seaboard line of highly expressive keyboards with the Blocks line of modular controllers. Some have been saying that the Seaboard Block is the point at which the Blocks line starts to make sense. Both there are more dots to connect. One is that ROLI also owns JUCE, which is fast becoming the tool of choice to develop music apps on multiple platforms, including mobile. Not sure how sophisticated JUCE’s MPE support is, but it does have some MPE-specific classes. Another point, mentioned in the comments on this interview, is that Bevin was instrumental in the MPE support in Moog’s Model 15 and Animoog synths on iOS. As these apps are quite influential, their continued development can have a big impact on the iOS part of the MPE scene.

      Speaking of iOS, the fact that the latest version of Audiobus can route MIDI could open up interesting possibilities. Jesse Chappell, developer of two MPE-savvy iOS apps (ThumbJam and DrumJam) has been teasing a forthcoming app which would somehow deal with MPE in a thorough way.

      And there’s a broader context for all of this. Hardware and software devices for electronic music (controllers, synthesizers, loopers, etc.) have been integrating into complete solutions. Several manufacturers have been doing both hardware and software. There aren’t that many hardware solutions for the sound output from MPE, but it’d only take a fairly simple box (maybe Arduino-based?) to allow much of the hardware synth world to receive MPE in an appropriate way (something which is already possible in software).

      So it really is a fascinating time to be getting into musical expressiveness through digital means.

  6. Feb 2017
  7. 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.

  8. 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.

  9. 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?

  10. 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?

  11. 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.