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As the teaser says, "Come for the reinforcement learning, stay for the GIFs." Stay for the short video, actually, to watch a human-shaped robot figure navigate complex landscapes. This aerticle summarizes the outcomes of a reserach paper (14 page PDF), It wasn't given instructions on how to do this; it learned how to jump and climb via reinforcement learning. "It's clear that DeepMind is using creative solutions to get around the obstacles it's presented with; much of the time, the movement that provides the most efficient solution isn't exactly natural looking."[Link] [Comment]
Como cada año, el Departamento de Proyectos Europeos del Instituto Nacional de Tecnologías Educativas y de Formación del Profesorado (INTEF) presenta el resumen del informe The NMC Horizon Report: 2017 Higher Education Edition que, producido conjuntamente por New Media Consortium (NMC) y EDUCAUSE Learning Initiative (ELI), identifica y describe las seis tecnologías emergentes que tendrán un impacto significativo en la educación superior en los próximos cinco años (2017-2021).
Además de esas seis tecnologías, en el informe original se analizan seis tendencias claves y seis desafíos significativos en educación superior, siempre atendiendo a tres plazos de adopción y resolución: a corto plazo (de 1 a 2 años), a medio plazo (de 3 a 4 años) y a largo plazo (de 5 a más años).
Unas tecnologías, tendencias y desafíos seleccionados y examinados por un grupo de 78 expertos de diferentes países en un proceso en línea, cuyo desarrollo y resultados quedan plasmados, como viene siendo habitual, en una plataforma wiki (http://horizon.wiki.nmc.org/).
Como novedad de esta edición, New Media Consortium presenta, en forma de tablas, una recopilación de las tecnologías, tendencias y desafíos recogidos en sus informes desde que la serie comenzara, allá por el año 2002. En definitiva, 15 años de cambios educativos propiciados, como no, por la evolución vertiginosa de las tecnologías.
Pero centrándonos en la edición de 2017, encontramos que muchas de las tendencias, desafíos y tecnologías se repiten respecto a la edición pasada. Realmente no se repiten, evolucionan, sobre todo en cuanto a las tecnologías se refiere. Esa es la clave. Por ejemplo, el aprendizaje móvil no presenta las mismas características ni el mismo potencial actualmente que hace algunos años, en absoluto. O las mismas analíticas de aprendizaje, un campo en continuo desarrollo y que buscan ser plenamente integradas en las próxima generación de Sistemas de Gestión del Aprendizaje (LMS).
Precisamente esas analíticas de aprendizaje son la base de uno de los desarrollos tecnológicos llamados a tener un gran impacto en la educación superior a corto plazo, las tecnologías de aprendizaje adaptativo (como ya se preveía en la edición de 2016). Junto a ellas encontramos el Mobile Learning, que sustituye a las iniciativas Trae tu propio dispositivo (Bring your Own Device, BYOD), contempladas el año pasado.
Los Makerspaces y la Realidad Aumentada y Virtual, tecnologías observadas a medio plazo en el informe de 2016, han sido reemplazas en el actual por el Internet de las Cosas y los Sistemas de Gestión del Aprendizaje (LMS) de próxima generación. Y, a largo plazo, la Inteligencia Artificial y las Interfaces Naturales de Usuario han ocupado el lugar de la Computación Afectiva y la Robótica (edición 2016 del informe).Descarga Resumen Horizon Universidad 2017. INTEF.
El original lo encontrarás aquí: The NMC Horizon Report: 2017 Higher Education Edition
Imagen de cabecera. Mobile Futures, por NYC Media Lab, en Flickr, con licencia CC BY-SA 2.0
Via Pacific Standard: “Government Watchdog Will Investigate Trump Administration on Civil Rights.”
Via Bloomberg: “Campus Rape Loses Special Status in Trump’s Education Department.”
Via The Washington Post: “Education Dept. closes transgender student cases as it pushes to scale back civil rights investigations.”
Via The New York Times: “Trump Move on Job Training Brings ‘Skills Gap’ Debate to the Fore.”
More on the business of job training in its own section below.
Via Inside Higher Ed: “Summer Pell Grants will be available to students beginning July 1, the Department of Education announced Monday.”
Via Inside Higher Ed: “The U.S. Department of Education on Thursday offered a first glimpse at how it is carrying out the Trump administration’s push to ease federal regulations – and asked for advice on what rules it should eliminate.” Among those regulations: FERPA. So that’ll be fun. More via The Hill and via the Department of Education’s press office.
Via The Chronicle of Higher Education: “Landmark Law on Higher Education Should Be Scrapped, DeVos Suggests.” That’s the Higher Education Act of 1965.
Via The Chronicle of Higher Education: “Here’s Every Major Statement Trump and DeVos Have Made on Higher Ed.”
There were so many falsehoods in Trump’s rally in Cedar Rapids, Iowa this week, that The New York Times had a “fact-check” in almost every paragraph of its coverage, countering the claims Trump made on stage. Edsurge runs with Trump’s promise to boost rural broadband like it’s a truth anyone can count on.
Tech CEOs visited the White House to talk about “modernizing” a.k.a. “technologizing” the government. “Apple CEO Tim Cook Urges Trump To Mandate Coding In Schools,” according to Edsurge. Google’s chairman Eric Schmidt praises Trump.
Via The Washington Post: “A teacher’s decision to be ‘visibly queer’ in his photo with President Trump.” Teacher of the Year indeed.
Via Inside Higher Ed: “The British government releases the results … of its new three-tiered rating system of teaching quality at universities.”
More on the politics of student loans in the student loan section below. And more on the US Department of Education activities in the campus section and HR section below.(State and Local) Education Politics
Via The LA School Report: “LAUSD approves $7.5 billion budget under cloud of declining enrollment and future cuts.”
“Louisiana Becomes First State to Ban the Box,” Inside Higher Ed reports. That is, to ban the box on an application (for a job or to a public college) asking about criminal history.
Via EdWeek’s Market Brief: “Sweeping New Fla. Law Set to Shake Up Charter School Landscape, Testing.”Immigration and Education
Via AZ Central: “Arizona Appeals Court overturns in-state tuition for ‘dreamers’.”
Via NPR: “For Some Students, Getting An Education Means Crossing The Border.”
Via Axios: “Trump plans to scrap rule allowing foreign founders into U.S.”
Via the BBC: “Accenture and Microsoft plan digital IDs for millions of refugees.” What could possibly go wrong?Education in the Courts
Via Nature: “One of the world’s largest science publishers, Elsevier, won a default legal judgement on 21 June against websites that provide illicit access to tens of millions of research papers and books. A New York district court awarded Elsevier US$15 million in damages for copyright infringement by Sci-Hub, the Library of Genesis (LibGen) project and related sites.” More via The Chronicle of Higher Education.
Via Inside Higher Ed: “Three major textbook publishers sue the bookstore provider Follett, alleging failure to stop selling pirated versions of their books.” The publishers in question are Cengage, McGraw-Hill, and Pearson.
Via The LA Times: “Lawsuit alleges hostile environment for Jews on San Francisco State campus.”
More on the legal battles of “Dreamers” in the immigration section above.Testing, Testing…
Via Chalkbeat: “Calculator mix-up could force some students to retake ISTEP, and Pearson is partially to blame.” ISTEP is the Indiana state standardized test.
Via The Dispatch: “Miss. Dept of Education fires testing firm after exams wrongly scored.” The testing firm in question: Pearson.The Business of Student Loans
Via Buzzfeed: “Betsy DeVos Picked A Student Loan CEO To Run The Student Loan System.” A. Wayne Johnson is the CEO of Reunion Student Loan Services. Nothing to see here… Move along…
Via Buzzfeed: “Public Service Loan Forgiveness Isn’t Working, Watchdog Says.”
Via CBS: “Here come higher student loan interest rates.”
Via the AP: “The nation’s largest servicer of federal student loans has lobbied against states’ efforts to license student loan servicers in Maine and elsewhere this year as it seeks to become the nation’s single servicer of student loans under a plan backed by U.S. Education Secretary Betsy DeVos.” That would be Navient Corp.
Via NPR: “Federal Officials Turn To Private Law Firms To Chase Student Loan Debtors.”
Research from New America says that “allowing borrowers to refinance federal student loans finds that most of the benefits of refinancing would be seen by a small number of households with relatively high debt.”The “New” For-Profit Higher Ed
For-profit Hickey College will close.
Via Inside Higher Ed: “The as-yet unnamed online university resulting from the proposed acquisition of Kaplan University by Purdue University has set discounted tuition rates for in-state students and free tuition for Purdue employees.”
Regulations regarding for-profit higher ed are too heavy-handed, according to an op-ed in Inside Higher Ed written by a member of the board of Walden University, a for-profit university.Online Education and the Once and Future “MOOC”
Via The Post and Courier: “South Carolina’s online charter schools: A $350 million investment with disappointing returns.”
“Students’ Rising Expectations Pose Challenge to Online Programs,” The Chronicle of Higher Education reports.Meanwhile on Campus…
Via NJ.com: “Charter school won’t pay teachers for final 2 months, union says.” The charter school, which is closing it doors, is the Merit Preparatory Charter School, run by “personalized learning” charter chain Matchbook Learning. (Here’s a sponsored article, paid for by the Gates Foundation and published by Edsurge promoting the school and its technology.)
Via The Lens: “Charter school kept two homeless children out of class for a month because they didn’t have uniforms.” That is the Sophie B. Wright Charter School in New Orleans.
Via The 74: “Montessori Was the Original Personalized Learning. Now, 100 Years Later, Wildflower Is Reinventing the Model.” (This reminds me that I need to write something about the history of Montessori and why all sorts of companies have appropriated the brand.)
Via The Chronicle of Higher Education: “Education Dept. Closes Title IX Investigation of Liberty U.”
Via The New York Times: “A College Built for Canadian Settlers Envisions an Indigenous Future.” That’s the University of Saskatchewan.
Via The New York Times: “Dallas Schools, Long Segregated, Charge Forward on Diversity.”
“Why So Many Top Hackers Hail from Russia,” according to information security journalist Brian Krebs. Spoiler alert: computer classes are required in school.
Via The Chronicle of Higher Education: “How Conservative Media Outlets Turn Faculty Viewpoints Into National News.”
Via The New York Times: “The Media Brought the Alt-Right to My Campus.”
Via The New York Times: “A Campus Argument Goes Viral. Now the College Is Under Siege.” That’s Evergreen State College in Olympia, Washington.Accreditation, Certification, and “Competencies”
Inside Higher Ed reports on the appearance of the Southern Association of Colleges and Schools and the Distance Education Accrediting Commission before a federal panel on accreditation.
Via CNN: “ The Girl Scouts are adding a cybersecurity badge.”
“The Competency-Based Education Network, a grant-funded group of 30 institutions with competency-based programs, has become a free-standing nonprofit association and is opening up its membership,” Inside Higher Ed reports.Go, School Sports Team!
Via The Chronicle of Higher Education: “U. of Oregon Athlete Played a Season While Under Investigation for Sexual Assault.” The athlete was Kavell Bigby-Williams, a UO men’s basketball player. “Mr. Bigby-Williams has been under investigation by the campus police of the Northern Wyoming Community College District since September 19, the newspaper said. He is accused of sexually assaulting a woman near Gillette College, where he was a student before transferring to Oregon, the Daily Emerald reported.” Fire Coach Dana Altman now.From the HR Department
The Chan Zuckerberg Initiative has hired Bror Saxberg to handle its “learning engineering” efforts. Saxberg had previously been the Chief Learning Officer at Kaplan (and Edsurge, when covering the news, fails to disclose its financial ties to Kaplan).
Via Education Week: “Teachers’ Union Faces Backlash Over Publication on Personalized Learning.”
Via Inside Higher Ed: “Staffing Woes at the Education Department.”
More on Department of Education hires in the student loan section above.
Via NPR: “At Yale, Protests Mark A Fight To Recognize Union For Grad Students.”
Via The Chronicle of Higher Education: “AAUP Considers Paying Adjuncts in Its Leadership Posts.”The Business of Job Training
This piece – “We Need to Rethink How We Educate Kids to Tackle the Jobs of the Future” – is a couple weeks old but I’m including it here nonetheless because of this priceless line: “The truth is, there is little taught in school that today can’t be handled with a quick Google search and an Excel spreadsheet.”
Via The Wall Street Journal: “German-Style Apprenticeships Simply Can’t Be Replicated.”
Via Andy Smarick, writing for the American Enterprise Institute’s blog: “Pumping the brakes on apprenticeships.”Upgrades and Downgrades
“Mark Zuckerberg just unveiled Facebook’s new mission statement,” says The Verge. It changes from making the world more open and connected“ to ”give people the power to build community and bring the world closer together." This wasn’t really what I was talking about, Zuck, when I talk about the ideology of personalization.
Via Buzzfeed: “ Violence On Facebook Live Is Worse Than You Thought.” Because, you know, Facebook’s mission is “community.”
Via Creative Commons: “Toward a Better Internet: Building Prosocial Behavior into the Commons.”
Also via Creative Commons: “Community update: Unsplash branded license and ToS changes.” Unsplash is a photo sharing website.
Via Edsurge: “How Amazon’s Purchase of Whole Foods Highlights the Hybrid, ‘Omnichannel’ Future of Higher Ed.” #NotTheOnion
Via The Wall Street Journal: “Media Startups Try a Lower-Cost Model: Unpaid Student Writers.”
Via The Verge: “Google Glass gets its first update in nearly three years.” Phew! Just in time for all those ISTE sessions claiming Google Glass is the future of education.
In other Google news, “Google Will Stop Reading Your Emails for Gmail Ads,” Bloomberg reports.
Stanford University’s Larry Cuban continues his analysis of behavioral management tool ClassDojo.
LMS news from Edsurge: “University of Michigan’s Gamified LMS Opens Up to Other Institutions.”
“Stale Words and Hackneyed Ideas That Make Edtech Investors Cringe,” according to an investor in Edsurge. Among those cringeworthy ideas: the LMS.
Via Bloomberg: “Mattel’s CEO Thinks Internet-Connected Toys Are the Future.”
“New houses will have Alexa and Wi-Fi built into the walls,” according to Mashable.
Via Buzzfeed: “Bill Cosby Is Going To Educate People On How To Avoid Sexual Assault Allegations.”
Via Pando: “Binary Capital’s Justin Caldbeck accused of unwanted sexual advances towards female founders. Where’s the outrage?” (Among those education companies in Binary Capital’s investment portfolio: Educents.)Robots and Other Ed-Tech SF
Via Edsurge: “Why a Robot-Filled Education Future May Not Be as Scary as You Think.” It’s also going to apparently be full of bullshit, made-up “statistics” about the future.(Venture) Philanthropy and the Business of Ed Reform
There’s HR news from the Chan Zuckerberg Initiative in the HR section above.Venture Capital and the Business of Ed-Tech
Behavioral management company Hero K12 has raised $150 million from BV Investment Partners.
Tutoring company Ruangguru has raised $7 million in Series B funding.
Lingokids has raised $4 million in seed funding from HV Holtzbrinck Ventures, Bessemer Venture Partners, Big Sur Ventures, JME Venture Capital, and Sabadell Venture Capital. The vocabulary game maker has made $5.15 million total.
Wonderschool has raised $2 million in seed funding from Cross Culture Ventures, First Round, Edelweiss, FundersClub, Lerer Hippeau Ventures, and SoftTech VC. According to the company description, “Wonderschool offers a platform where people can start infant and toddler programs and preschools out of their homes.”
Hugsy has raised $226,460 in seed funding from the Leapfunder European angel investor network. Hugsy makes a “smart baby blanket.” (Yes, I’m tracking on this sort of thing as part of my 2017 “Top Ed-Tech Trends.”)
Carson-Dellosa has acquired Rourke Educational Media.Privacy, Surveillance, and Information Security
Congrats to the education company Road Scholar for appearing in this Gizmodo story about how companies surreptitiously collect your data. “Before You Hit ‘Submit,’ This Company Has Already Logged Your Personal Data.”Data and “Research”
Via investment analysis firm CB Insights: “The Ed Tech Market Map: 90+ Startups Building The Future Of Education.” The map isn’t that useful, to be honest. The list of which education technology companies have raised the most money is more so.
Via Education Week: “Online Classes for K–12 Students: 10 Research Reports You Need to Know.”
Via IRRODL: “Khan Academy as Supplemental Instruction: A Controlled Study of a Computer-Based Mathematics Intervention.”
Via IHE blogger Joshua Kim: “The Institutional Impact of Maryville’s 1:1 iPad Program.”
Via Inside Higher Ed: “Last year Achieving the Dream began a $9.8-million project to use open educational resources (OER) to create degree programs at 38 community colleges. A study on early returns, which was conducted by SRI International and the rpk GROUP, found that faculty members are changing their teaching in the OER courses and that students are at least as engaged in the courses as they are in conventional ones.”
Via The Chronicle of Higher Education: “5 Cocktail-Party-Conversation Findings From the Latest Survey of College Presidents.”
Speaking of cocktail party conversations, The Hechinger Report notes that “Unlike the students they oversee, most college presidents are white and male.”
Education Next publishes an excerpt from Daniel Willingham’s new book The Reading Mind: A Cognitive Approach to Understanding How the Mind Reads.
Via Edsurge: “Low Income and Looking For a Successful School. Study Shows Choices Are Slim.”
Via Inside Higher Ed: “Measuring Learning Outcomes From Military Service.”
Via Education Week: “Immersive Tech, Virtual Reality Market to Soar Worldwide, New Analysis Predicts.”
“Published in 2008, ‘Disrupting Class: How Disruptive Innovation Will Change the Way the World Learns’ predicted that the growth in computer-based delivery of education will accelerate swiftly until, by 2019, half of all high school classes will be taught over the Internet,” writes EdTech Strategies’ Doug Levin, asking “Are We On Track?”
(For what it’s worth, I’m tracking all these predictions about the future at predictions.contrafabulists.com.)RIP
Via The Washington Post: “Otto Warmbier dies days after release from North Korean detention.”
Gary Stager pens an obituary for Bob Tinker who passed away this week. A proponent of constructivist learning (particularly with regards to science and technology), Tinker created “probeware” and founded the Concord Consortium, among many other contributions to the field of ed-tech.
Icon credits: The Noun Project
These were my remarks as a guest speaker in Donna Murdoch's class “Online Teaching and Learning – Applying Adult Learning Principles” this evening. I was asked to speak about learning analytics, but like I said in my keynote last week at NMC, ed-tech is boring. So this is a talk about pedometers.
“Know thyself” – this is an ancient maxim, of course. But it’s become not so much a philosophy of introspection or reflection but a compulsion for data collection and data analysis. We now live in a culture of quantification. (We have for a while now, no doubt.) All this is aided today, no doubt, by new computing technologies that create and collect massive amounts of personal data.
Learning analytics, in some ways, is a symptom of this data-driven culture – one that also is not new to education. Learning analytics are technologies that support and reflect the idea that we can collect and measure and analyze data about learners in order to know what they know, in order to optimize what and how they learn.
I want to invoke the guest speaker’s privilege and talk about something slightly different than what I was asked to speak about: that is, learning analytics. Now, I hope you’ll see that almost everything I say is very much related to learning analytics and to education technologies more broadly – to how we’re asked to hand over our personal data to various hardware and software companies, to our employers, to the government, to our schools under the guise of better “outcomes,” more productivity, and so on.
I want to talk a little bit about fitness trackers this evening.
“Wearables,” for what it’s worth, were featured in the 2016 Horizon Report for K–12, an annual report that predicts which education technologies are “on the horizon.” The “Quantified Self” appeared on the 2014 Horizon Report for Higher Education. In both cases, the Horizon Report predicted these technologies were four to five years from widespread adoption.
You hear these sorts of predictions all the time – that everyone is going to own or use X, Y, or Z technology in the next few years – but according to a recent study, only about 10% of Fitbit owners (and that’s of the less than 12% of US consumers own fitness trackers) are still wearing the device after a year.
Beware the marketing hype.
Like all technologies, fitness trackers have a history – one that certainly predates Fitbit or Jawbone or the Nike Fuelband.
There’s some debate about who invented the first pedometer, which remains a core functionality of most activity trackers: that is, counting how many steps one takes per day. Wikipedia lists three possible inventors: Leonardo da Vinci, who sketched the design for a gear-driven device with a pendulum arm that would swing back and forth with every walking leg motion and measure distance traveled; Abraham-Louis Perrelet, a Swiss inventor who built a self-winding watch in 1770 that wound when the wearer walked and then built another device, based on that watch, in 1777 that could measure walking distance; and Thomas Jefferson (Americans do like stories in which we feature prominently in the invention of things, don’t we), who purportedly brought the first pedometer to the US, although it’s not known if he ever improved on the design as he never filed any patents for his inventions. A website that reviews fitness devices also suggests that Jean Fernel, a French craftsman, might have invented the first pedometer in 1525 or Robert Hooke, an English scientist, might have in 1674, or Hubert Sarton, another Frenchman, might’ve in 1778. It was John Harwood, a British man, who was awarded the first patent for a pedometer in 1924. So even if we date pedometers from that patent, we’re still looking at about 100 years of history; if we credit da Vinci, we’re looking at about 500 years of pedometers.
500 years, and still less than 12% of Americans own a fitness tracker. Be a little skeptical of those who insist that technologies are changing faster than ever or that we’re adopting new technologies more quickly than ever before.
Now, it’s worth asking why so many inventors have been interested in the pedometer concept. For these men I’ve just named, at least, their interest was not in improving “fitness” per se but in measuring distance. For da Vinci, the device had military applications; he also imagined it would help improve mapping.
The promotion of the pedometer as a fitness device started in the 1960s when Dr. Yoshiro Hatano, a professor at the Kyushu University of Health and Welfare, undertook some applied research into exercise and calories. Concerned about the rise in obesity in Japan and wanting to promote and reinforce daily activity as part of “good health,” Hatano began selling a device known as “Manpo-kei” – the 10,000 steps meter. Hatano had calculated that the average Japanese person walked about 3500 to 5000 steps a day. By increasing the number of steps to 10,000 (roughly 5 miles), the amount of calories burned obviously would increase as well – up to about 500 calories a day, which could translate into about 20 kilos of weight loss in a year, he claimed. 10,000 steps was, according to the marketing for the Manpo-kei, ideal.
There are plenty of reasons to question that claim. 10,000 steps is less some medically-advised threshold than it is a marketing gimmick. Hatano could have picked 7500 steps or 13,333. 10,000 steps is a nice round number, one that will take you about 100 minutes of moderate activity to accomplish – but it’s also an arbitrary number. 10,000 steps is a goal that’s based on a lot of assumptions about bodies and activity and physical ability too. Nevertheless the number – and the connection between “steps” and “fitness” – has stuck with us for 50 some-odd years now. 10,000 – that’s the goal that almost all fitness trackers set for us.
And so, we can debate whether or not measuring “steps” is the same as measuring “fitness.” But we should ask too: How well do these devices actually track “steps”? (Rather, how accurate are they in counting “steps” and converting all our physical activity into “steps”?)
Surprise, surprise. They’re far from perfect. It depends on where you wear the device – on your wrist, in your bra, in your pocket, in your purse. It depends on what kind of activity you undertake. A study published in 2013 found that these devices tended to underestimate the energy expended while standing or bicycling or jogging uphill. And it depends on the device, the brand. A recent study from Stanford found that six out of seven wristband activity monitors measured heart rate with an error rate of less than 5%. Not too bad. But none of these monitors measured energy expended – a.k.a. calories – accurately. The most accurate fitness device was off by an average of 27%. Off, in other words, by roughly one McDonald’s Cheeseburger.
These errors are pretty important if you’re making decisions about your diet based on the data you glean from your fitness tracker– like should you have a McDonald’s Cheeseburger or another glass of wine. These errors are really important if someone else is making decisions about you based on this data – like your employer deciding whether your participation in the company wellness program is adequate. Or your health insurance company deciding whether to deny you coverage based on your physical activity or lack thereof. Or your school tracking how much you exercise and what you eat and how much (and where) you sleep and giving you a grade for it.
Oral Roberts University, for example, beginning in the spring of 2016, encouraged its incoming students to wear a Fitbit and urged them to log their personal data in the learning management system.
Also in 2016, the University of Michigan signed a $170 million deal with Nike. One provision of the contract allows Nike “to harvest personal data from Michigan athletes through the use of wearable technology like heart-rate monitors, GPS trackers and other devices that log myriad biological activities.”
Are these examples of “learner data”? They’re certainly examples of “student data,” right?
Whose data does the data collected by a fitness tracker belong to? What do the Terms of Service say? (You’ve read the Terms of Service, right?) What else, in addition to how many steps a wearer has taken in a day, do these devices track? What does the fitness tracker maker use this data for? Who does the fitness tracker maker share the data with? Who does the fitness tracker maker sell the data to? How long does the company retain it? Can a user request a copy of their data? Can the user delete it? These aren’t medically-approved devices, of course, but what is being collected is, no doubt, sensitive health data. Is that data safe, secure, private? Are there any legal protections regarding this data – that is, does it count as part of someone’s “medical record”?
What are the implications when we compel people – through health insurance or through employment or through the learning management system – to be monitored in this way?
The marketing tells us that this sort of tracking should be done for our own good, for our health and well-being. We should want to track and be tracked. The science? Well, the science, not so much. Indeed, one study published last year in the journal of the American Medical Association, found that those who wore fitness trackers lost less weight than those who did not.
Yes, that’s just one study. I hear a lot of people say – anecdotal data – that they like their fitness tracker because it motivates them to move. They say they like the “gamification” of exercise – earning points and badges, sharing their efforts via social media, and so on. They insist they need this extrinsic motivation as their intrinsic motivation simply isn’t enough. Not 10,000 steps worth of enough, that is.
And Americans have been tracking calories for quite some time now. Again, there’s a history here – why the calorie is the unit of measurement. Like the invention of the pedometer, there are many origin stories we could tell here – the development of the science of human nutrition in the early twentieth century. I’ll give you one name (because I’ve only mentioned men so far): Lulu Hunt Peters, an American doctor, who published the bestselling diet book Diet & Health: With Key to the Calories in 1918 and who popularized the idea that if you counted calories, you can lose weight.
500 years of pedometers. 100 years of counting calories. 50 years of connecting “steps” and “fitness.” Today’s fitness tracker isn’t new, but rather fits quite neatly into a long social and technological history. We are very accustomed to the stories about measuring these data-points for the sake of our personal health and well-being. There’s a cultural logic to the fitness tracker.
Of course, as the familiar saying (often misattributed to Einstein) goes, “Not everything that counts can be counted, and not everything that can be counted counts.”
Is this meaningful data? Are “steps” or “calories” meaningful units of measurement, for example? What can we truly know based on this data? Are our measurements accurate? Is our analysis, based on the data that we’ve collected, accurate? What sorts of assumptions are we making when we collect and analyze this data? Assumptions about bodies, for example. Assumptions about what to count. Assumptions and value judgments about “health”. How much is science, and how much is marketing? Whose data is this? Who owns it? Who controls it? Who gets to see it? Is this data shared or sold? Is there informed consent? Are people being compelled to surrender their data? Are people being profiled based on this data? Are decisions being made about them based on this data? Are those decisions transparent? Are they done via algorithms – predictive modeling, for example, that tries to determine some future behavior based on past signals? Who designs the algorithms? What sorts of biases do these algorithms encode? How does the collection and analysis of data shape behavior? Does it incentivize certain activities and discourage others? Who decides what behaviors constitute “good health”?
Those are questions we should consider regarding fitness trackers, sure. But they’re questions for all sorts of technologies – education and otherwise.
Please ask these questions when you hear the marketing for “learning analytics.” I’m going to re-state that previous paragraph:
Is this meaningful data? Are “test scores” or “grades” meaningful units of measurement, for example? What can we truly know based on this data? Are our measurements accurate? Is our analysis, based on the data that we’ve collected, accurate? What sorts of assumptions are we making when we collect and analyze this data? Assumptions about bodies, for example. Assumptions about what to count. Assumptions and value judgments about “learning”. How much is science, and how much is marketing? Whose data is this? Who owns it? Who controls it? Who gets to see it? Is this data shared or sold? Is there informed consent? Are people being compelled to surrender their data? Are people being profiled based on this data? Are decisions being made about them based on this data? Are those decisions transparent? Are they done via algorithms – predictive modeling, for example, that tries to determine some future behavior based on past signals? Who designs the algorithms? What sorts of biases do these algorithms encode? How does the collection and analysis of data shape behavior? Does it incentivize certain activities and discourage others? Who decides what behaviors constitute “a good student” or “a good teacher” or “a good education”?
Are learning analytics (or fitness trackers) a way one can “know thyself”? What do we think we know, based on them?