MOOCs, Educational Technology, and an Oxford thesis

Last year I completed an MSc at the University of Oxford, where I wrote my thesis on MOOCs. This post talks a little bit about my research and why I think it’s important.  The full version of my thesis can be found here, and an abridged version here.examschools

What a difference a year makes.

The New York Times proclaimed 2012 the ‘Year of the MOOC.’  Massive open online courses, with their hard-to-take-seriously acronym ‘MOOCs’, had become the fascination of New York, Silicon Valley, and thousands of universities in between.  As university officials scrambled to hop on board, a debate was brewing over the efficacy of MOOCs.  While some technologists and educators were predicting a revolution in higher education, others warned of displaced professors and for-profit education run amok.

Fast forward a year.  As the first studies and analyses about MOOCs have since been published, much of the hype has abated.  As it turns out, retention rates have been low, usually between 10-15%, and MOOC students are more likely to be well-educated than disadvantaged, despite the rhetoric of accessibility and openness.  Even Sebastian Thrun, CEO of Udacity, one of the leading MOOC platforms, has acknowledged the shortcomings of current MOOCs.  This dampened rhetoric is a welcome change—these technologies are young and need improvements—but MOOCs remain, in my view, an incredible opportunity for improving education.

I happened to be searching for a dissertation topic while this debate was unfolding last year.  I arrived at Oxford intending to study the effects of personalization and algorithmic filtering on political discourse but became more and more interested in education and the growing debate around MOOCs.  Faced with an impending deadline to declare a topic, I chose the education route because I believed there was more to contribute in this new and emerging area of study, one that remains critically important as we face stagnant educational outcomes across the US.

My challenge was finding an appropriately scaled research question within the context of MOOCs, which was particularly difficult given the lack of existing research.  Retention rates caught my attention.  Why were so many students dropping out of MOOCs?  Was this an indication that MOOCs weren’t working, or were the numbers missing something?

What are MOOCs?

Massive open online courses attempt to deliver high quality educational content in a digital, and therefore highly scalable, environment.  MOOCs use two primary tools to accomplish this goal: 1) modular lectures and assessments, optimized for ‘mastery learning’; 2) online communities for peer-support and peer-grading.  Let me unpack those a little bit.

MOOCs are designed to make learning a more personalized experience than traditional in-classroom experiences.  The learner may proceed at their own pace, progressing to the next lecture or assessment only when they are ready.  Lectures are ‘modular,’  meaning that they are broken down into small, self-contained segments usually between 8-12 minutes.  Each lecture is accompanied by a short assessment to check for understanding.  This course design aims to provide flexibility for the learner and achieve ‘mastery learning,’ a pedagogical method that stresses understanding over progress.  In this context, learners are encouraged to understand each learning unit completely before progressing to the next.  In a famous study, Benjamin Bloom demonstrated that mastery learning can result in a one standard deviation improvement in learning outcomes compared with traditional instruction.

Although computers may excel in providing a personalized learning experience, they struggle to provide human interaction.  To an extent, there may be no remedy to this shortcoming, but MOOCs are borrowing features from social networking sites and using them to provide an element of peer interaction while maintaining their massive scale.  MOOCs rely largely on online communities that interact through message boards and forums.  Students interact with each other and answer questions, provide feedback on assignments, and in some courses, grade each other’s work.

Taken together, these two characteristics provide a foundation for most MOOCs.  Having said that, there are many variations in the specific structure and content of MOOCs, and each of the major platforms has taken a different approach.  If you really want to learn more about MOOCs, you should try one!  Coursera, edX, and Udacity are all good places to start, and they’re free.

Where are MOOCs headed?

The more I learned about MOOCs, the more excited I became.  But I kept returning to the question of sustainability.  If MOOCs are typically free to students, how can they earn enough money to be financially self-sufficient?

The first answer is that they don’t have to, not yet.  Coursera and Udacity are both generously funded by (mostly) Silicon Valley venture capitalists.  Their funding model allows a great deal of flexibility in the early years of the investment, where the platforms will be able to operate at a loss while they scale their platform and user base.  edX, meanwhile, is a non-profit funded by MIT and Harvard.  Although both schools have indicated their preference for a financially sustainable model, their endowments are more than sufficient to fund the platform as long as it aligns with their educational missions.

The major MOOC platforms in the US, therefore, won’t need to become financially sustainable overnight—but the clock is ticking.  In response, each of these platforms has experimented with various revenue models.  Udacity has developed a partnership with Georgia Tech to offer a Masters in Computer Science through their platform.  Students will pay roughly $7000 in tuition (a fraction of the cost of the in-person degree), of which Udacity will earn 40%.  edX charges universities a fee to offer certain types of courses on its platform.  Coursera is experimenting with a program called Signature Track, which provides verification services for a small fee charged to students.

There is a strong economic argument to be made that MOOC business models will converge on one in which their technology is embedded into existing educational models (I make the argument in an earlier paper, available here).  If that is the case, then students will be paying to access content either directly, to the MOOC platform, or indirectly, through their tuition to the traditional educational institution.  And this brings us back to retention rates.  Will people really pay for a service that successfully graduates less than 10% of its enrollees?

The trouble is, those retention rates are based on courses where students can enroll for free, with just a couple of clicks.  There are no costs to enroll and no costs to drop out.  Is this a fair comparison?  Can the value of MOOCs be judged based on their free enrollment and in order to evaluate their efficacy within existing educational models?  I didn’t think so.  I wanted to find a better way to evaluate MOOCs, one that evaluated student behavior in a context more analogous to the environments I suspected MOOCs might inhabit in the future.

The Research Plan

In early 2013, the University of Pennsylvania offered a course called “Calculus: Single Variable” (CSV).  CSV was one of the first Coursera courses to offer Signature Track, an optional addition to the standard course that gives students the opportunity to earn a “Verified Certificate”.  For a fee, $49 in this case, students have their identity verified throughout the course and receive a “verifiable electronic certificate” upon completion.  This verification makes the certificate more valuable to students, but since the course content itself remains unchanged, it also provides an opportunity to study MOOCs in an environment where students are paying for access.  Moreover, since Signature Track students take the course at the same time as free students, it provides an opportunity to study the difference in student behavior between the two groups.

There were two main components to the research.  In the first, I developed a set of metrics for evaluating student behavior in MOOCs, metrics that were better calibrated to the specific characteristics of MOOCs than existing metrics, which had been borrowed from other disciplines.  In the second, I used a series of quantitative analysis methods to examine the course data from CSV for differences in student behavior between the Signature Track and non-Signature Track cohorts.

The Results

My analysis demonstrated significant differences in student behavior between the paying students (Signature Track) and those taking the course for free.  Across the board, paying students were more likely to complete the course and score well in exams than their non-paying classmates.  Signature Track students engaged with four times as much content, exhibited ten times higher persistence, and achieved seven times higher grades on average than Non-Signature track students.  Most importantly, Signature Track students were 25 times more likely to pass the course.

(Please see my thesis for details on results)

Why is this important?

As my research progressed, it became clear that the pendulum of public opinion was moving away from its previously exuberant perception of MOOCs.  The reasons for this shift are complex and varied.  There are valid reasons for a retreat from the over-hyped predictions of 2012, but the debate is also embedded in wider conversations about education reform, education technology, and politics.  These larger debates involve constituents either deeply invested in the status quo or committed to its dissolution.  They have, on both sides, co-opted the conversation about MOOCs to fit their interests.

Perhaps the most vivid example of this conflict is the debate about education technology.  For some, education technology offers an opportunity to revolutionize the classroom and improve the educational outcomes for millions of students who desperately need it.  For others, education technology distracts from the real needs of students: quality teachers, safe classrooms, and better systems of social support.  To the first group, the other seems deeply invested in a failing status quo.  The second group, meanwhile, sees its opponents as profiteers of a crumbling system.

The MOOC conversation has become ground zero for this conflict and attracted powerful supporters to each side.  On one hand, proponents of MOOCs and educational technology are widely aligned with the technology industry, it’s venture capital backers, and certain elements of the educational reform movement.  On the other, opponents (or at least vociferous critics) of MOOCs and educational technology often align with teachers unions, as well as those critical of education reform.  There’s far more nuance to this debate than I can sufficiently explain in this post—it’s a complicated environment—but suffice it to say that each side brings substantial resources to the table.

The debate about MOOCs has split largely along these lines.  As in any debate, each side has adopted its own set of statistics and numbers that best support its position.  Proponents cite enrollment numbers in the millions without acknowledging how many of those students never show up to class.  Opponents cite low retention rates without acknowledging how many students do pass these courses (even a small percentage of a really big number is a big number).  My research tried to develop a more neutral understanding of MOOC outcomes.

In the course I studied, over 66,000 students enrolled to take the course.  This is that big number that technologists love, but only about 29,000 students ever watched a video or took a quiz.  Of these students, only 611 finished, an especially low retention rate even for MOOCs.  This is that low number that opponents of educational technology love, but it fails to include any indication of student intent.  Of those students that indicated a high degree of intent by paying for the course, 57% (76/133) passed.  My research also shows that an additional 3,600 students watched most of the videos for the course but didn’t take any quizzes.  These students didn’t pass, but are we to say that they didn’t gain anything by watching the lectures?

The MOOC debate is just beginning.  We may ultimately stop calling them MOOCs (I’d be ok with that), and the environment in which students encounter them may change, but their core function and the technology that enables it isn’t going anywhere.  We need to ground this important debate in meaningful numbers, numbers that reflect what’s actually happening in MOOCs.  I think my thesis took a few humble steps toward that goal.

Teaching music to our kids…it’s not pointless.

141286730_05699b0e44_zMark Oppenheimer’s recent piece in The New Republic likened learning the violin to playing foosball and equates ‘pointless’ music lessons with his annual viewing of Dazed and Confused. Perhaps realizing he had missed the mark, or at the very least been misunderstood, he later wrote an apology. But his apology fails to address the faulty premise of the original article.

Mr. Oppenheimer proposes a simple test to judge the usefulness of music lessons:

“Go on Facebook and ask your friends to chime in if, when they were children, they took five years or more of a classical instrument. Then ask all the respondents when they last played their instrument.”

Maybe a few will chime in, maybe none. He’s suggesting that if we won’t do something in adulthood, we shouldn’t have our kids learn it during childhood.

Now, ask your Facebook friends if they use calculus or recite Shakespeare regularly in their adult lives. Mathematicians and english professors notwithstanding, you won’t hear much. But we wouldn’t extend his argument to math and literature, would we? Of course not, because learning calculus and Shakespeare is important not only for the content we absorb, but because it changes how we think. Only by understanding math and literature can we appreciate how science and culture evolved to their present moment. And in the sometimes painful process of learning, we develop the tools necessary to make our own contributions.

The same holds true for music. Learning an instrument is difficult and there can be no guarantee that kids will continue to play throughout their adult lives, but the process of learning music itself has value. And not just for the appreciation of music, but for the hours of practice and patience required to learn a musical instrument. Anything worth doing takes years to master, and our kids won’t come to understand that playing foosball.

Threats and Opportunities for Journalism Online

Rasmus Nielsen is post doctoral research fellow at the Reuters Institute for the Study of Journalism at the University of Oxford.  The following is a reflection on his lecture at the Oxford Internet Institute on Feb 13, 2013.

What does the Internet mean for journalistic content creation and the business model that supports it?  Rasmus Nielsen attempted to shine some light on the threats and opportunities posed by the shift to online journalism.  His talk focused on the threats but was informative nonetheless.

He draws an important distinction between the effects of online journalism on individual journalists, the organizational norms of journalism, and the journalism industry as a whole.  As he explains it, the Internet has increased the capabilities of individual journalists in a transformative way.  The access to information and means of communication available to the individual journalist today are far superior than what they were in the past.  These new capabilities have become the norm within news organizations.  Journalists are expected to get answers quickly and produce content in time with the quickening pace of 24-hour media organizations.  This has mixed effects, Nielsen says, as rapid digital content creation crowds out more traditional journalistic practices.

Where the effects of the Internet on individual journalists and news organizations have been either positive or mixed, Nielsen sees its effects on the industry as largely negative.  The traditional business models that supported journalistic content creation are crumbling; whatever online revenue these organizations are capable of generating cannot keep pace with declines in print revenue.

Although Nielsen was quick to point out that there are reasons for optimism—he used the NYTimes coverage of the 2012 election as an example of the richness and depth that new media journalism can offer—he maintains that the search for a single replacement for print revenues is ultimately pointless.  This is especially true with respect to younger generations, who expect content to be available anytime and for free.  The production of the content that we expect continues to be funded by print revenues, which are in a seemingly endless decline.  To paraphrase Nielsen, the media environment we enjoy—free content, anytime—is financed by the media habits of our parents.

Nielsen’s most interesting point was about the alternative revenue sources available to news organizations.  If revenue from paywalls and online subscriptions are unable to keep up with declining print revenues, what can news organizations do to sustain their content production?  Nielsen suggests they experiment and build a diversified portfolio of revenue opportunities.  They might take a cue from the music industry and focus on building their brand around events and communities.  Nielsen believes there is still time to get this right and that in this transitional period, experimentation is crucial.

The idea of events—think speaker series or conferences—run by major news organizations is an interesting one.  That may not help the El Dorado Hills Telegraph, though, or the Sacramento Bee, to name just a few of many small market newspapers struggling to stay afloat.  There are but a few news organizations with brands strong enough to command an audience on their own.

The news organizations that have survived this first shift in the media landscape are strong brands, like the New York Times or The Guardian, and specialty publications, like the Wall Street Journal or The Economist, which cater to a niche but valuable audience.  It remains to be seen whether broadly focused, quality journalism aimed at sustaining civic engagement can survive.  For small, local papers in particular, the prospects look bleak.  But as with any major disruption, opportunities exist for innovative business models and creative methods of content creation.

The Signal and the Noise by Nate Silver [Book Review]

signalnoiseWhat happens when you predict the winner of all 50 states in the presidential election?  If you happen to write for the New York Times, you become famous.  Indeed, you become a celebrity statistician.  (Yes, it’s a real thing.)  Nate Silver did just that in 2012.  He correctly predicted the winner of each state and became famous.  As Rachel Maddow of MSNBC put it, “You know who won the election tonight? Nate Silver.”

Nobody thinks this is more ridiculous than Nate Silver himself.  In interviews after the election, he was quick to point out that an eighth grader could have predicted about 40 of the 50 states.  The other swing states became increasingly clear as Election Day drew near, despite pundits on both sides predicting a nail-biter.  Silver held his prediction in perspective and with humility.

Humility in prediction is the theme of Silver’s book.  He describes a host of examples where predictions were made with inappropriately high levels of confidence.  At times, as in the financial crisis, there were disastrous results.  Silver sees this as a growing problem caused by the emergence of “big data.”  Given an exponential increase in the availability of data, the ability to extract the signal from the noise becomes increasingly important, and failure to do so efficiently can have serious consequences.  Complex systems, like the climate or the economy, are incredibly difficult to predict either because we lack the necessary data or because we lack a theory to make sense of the data.  At no point does Silver suggest we should stop making predictions, he simply (and wisely) advises that we make and consume predictions with greater humility and understanding.

The math underlying Silver’s approach is called Bayesian statistics.  Rather than attempt to remove all bias from statistical computation, Bayesian statistics accepts that our initial observations will be biased and flawed.  It is a probabilistic approach to prediction that moves incrementally forward, constantly iterating towards a more accurate prediction.  The alternative method of statistics, which you were probably taught in undergrad stats (called Fisherian or frequentist statistics), takes a more deterministic approach to statistics.  Frequentist statistics uses significance tests and methods like regression to build models that explain a phenomenon or system.  To Silver, these approaches delude statisticians into believing their models are unbiased and holistic.  Bayesian methods take an initial prediction or probability and update it using new pieces of evidence.  Bayesians believe that regardless of the accuracy of the initial probability (called the “prior”), Bayes theorem will move a prediction incrementally closer to the truth.  As Silver says, “it is…a statement—expressed both mathematically and philosophically—about how we learn about the universe: that we learn about it through approximation, getting closer and closer to the truth as we gather more evidence.” 

The Signal and the Noise is an enjoyable and thought-provoking read.  Silver is adept in explaining mathematical concepts in an accessible way and showing how they apply to real examples.  Most of these examples, which include the financial crisis, climate change, poker, baseball, and earthquake science, are well illustrated, insightful, and relevant.  He goes an example too far, however, when he tries to explain how the probabilistic approach could be used in national security strategy.  Here, Silver is out of his depth.  Otherwise, it was a great read and one that I’d recommend to anyone with an interest in prediction, data, and making sense of a messy, complex world.

Silver concludes with a clever play on the Serenity Prayer:

Distinguishing the signal from the noise requires both scientific knowledge and self-knowledge: the serenity to accept the things we cannot predict, the courage to predict the things we can, and the wisdom to know the difference.

The “Usefulness” of Patents and Copyrights

What does it mean to be useful?  IP law once provided protection for “useful” works of invention, innovation, and information.  Today, it is useful for preserving the interests of large, powerful rights-holders, often at a cost to creators, consumers, and the economy.  IP law should be made “useful” once more.

CopyrightWestern copyright finds it’s philosophical roots in two documents, the Statute of Anne and the U.S. Constitution.  The Statute of Anne, which was enacted by the British Parliament and predates the Constitution by almost eighty years, provides the protection of copyright “for the encouragement of learned men to compose and write useful books.”  The Constitution, no doubt borrowing from the Statute of Anne, secures for authors and inventors the exclusive right to their work, in order “to promote the progress of science and the useful arts.”  These documents both explicitly qualify their protection as governing only those works that may be called “useful.”  Why?

Intellectual property law is designed to promote economic progress.  If the law can protect the right of innovators to profit from their work, there will be a strong incentive for future innovation.  It’s a sound theory, but modern IP law has lost its way.  The role of IP law in promoting useful innovation is diminishing.

Technically, there is still a usefulness requirement in U.S. IP law.  New inventions must be deemed useful to earn a patent.  But we ought to be asking, “useful to whom”?  Where patents were once used to reward innovators, they are now often used by large companies to restrict competition.  Is Apple’s patent of rounded corners on the iPad really useful to consumers or to future innovation?  Or is it just protection against future competitors, like Samsung?

The usefulness distinction is even more important in copyright.  Copyright incentivizes the creation of information goods in the same way that patents incentivize the creation of physical goods.  But there is an important difference between information goods and physical goods that should change how we measure the economic value of copyrights and their usefulness.

Information goods are non-rival.  If you know something and explain it to me, my new knowledge doesn’t diminish yours.  There are no marginal costs for distributing knowledge from one person to another (or to a thousand others).  Therefore, any cost imposed on the distribution of information goods is economically inefficient.  Copyrights impose such a cost, as they require payment to access information for which the marginal cost of distribution should be zero.

By pointing out this inefficiency, I don’t mean to argue that copyrights should be discarded.  Taxes are economically inefficient as well but there are strong arguments for reasonable taxation, and we as a society have decided that they are necessary.  But we have to consider the burden these costs impose on the production of new information goods.

The creation of information goods requires two things: the time and ingenuity of a knowledge producer and the input of other information goods.  By creating additional costs for access to information goods, like expensive fees to academic databases, we’ve constrained the production of future information.  This counterintuitive effect is one of the negative externalities of copyrights, and it’s all too often overlooked.

The time and ingenuity of knowledge producers needs to be rewarded; they deserve a mechanism to recuperate the opportunity costs of their work.  However, the copyright system as it exists today has been coopted by the interests of large, commercial rights-owners.  For example, the copyright on works published in the U.S. now runs for seventy years after the death of the author.  Copyright for that duration does little to reward the author; any royalties go to the rights-owner instead, which is likely to be a publishing label.  Instead, it imposes significant costs on the aggregate production of future information goods.

Again, we should ask ourselves, “useful to whom.”  Does a seventy-year copyright “promote the progress of science and the useful arts”?  Or does it present an obstacle to further progress?

Intellectual property law must be recalibrated to a standard of usefulness that prioritizes incentives for creativity and innovation.  Patents and copyrights should reward innovators and knowledge producers.  They should not be used as weapons in ever-escalating corporate feuds.  Nor should they be used to extend the ability of corporate rights-holders to profit from the creativity of others.  When that happens, when IP law is useful only to the large, well-lobbied few, we all suffer as a result.  In a global economy where innovation drives economic growth, getting this question right couldn’t be more important.

If interested, The Wealth of Networks by Yochai Benkler and Remix by Lawrence Lessig are great books that include discussions of the shortcomings of today’s IP systems.  Benkler’s work informs my discussion of the economic inefficiencies of copyright and Lessig’s many books on the subject first introduced me to IP law.

First in His Class: Bill Clinton biography by David Maraniss [Book Review]

It was during the Democratic National Convention in September that I saw Bill Clinton work his magic.  He stole the show from President Obama that night; I’ve never seen a speaker connect with an audience like that.  For many my age, I think it was the first time we’d seen him demonstrate his political skill as adults.  Impressed as I was, I wanted to learn more.  So I picked up his biography by David Maraniss.  It covers Clinton’s life from his birth until the day he announces his candidacy for President.  The book was superb, and I’d highly recommend it.  Here are themes that stood out to me.


Bill Clinton was an extrovert.  I mean extrovert in the sense that he thrived on interaction with others; it’s what gave him life.  Where other politicians grew weary during long campaigns on the road, Clinton couldn’t get enough. Again and again one of Clinton’s acquaintances from his campaigns would confess to the power of his presence, that he was able to make people feel like they’d been friends forever.  This was one of his great gifts, and one that he used to his political advantage.  Clinton maintained extensive card files on everyone he met during his campaigns.  Over the course of his political career, this catalogue grew to include addresses, phone numbers, dates of last contact, donation amounts, and other facts for thousands of people.  It was both a compulsion and a calculated political move.

Curiosity about the people around him was one of his strongest traits, the main intersection of his gregarious, empathetic personality and his political ambition.


Clinton knew that politics was his calling.  From high school on, every decision he made was calculated to maximize his long term political viability.  In this respect, he was often calculating and hollow; a friend today might be sacrificed tomorrow if necessary.  The sense of purpose he demonstrated is exceptionally rare, I think.  Most of us take longer to figure out what we’re called to do, if we ever do.  It’s a fascinating thing to observe nonetheless–someone consumed with a single purpose.

Political skill

Time and again Clinton exhibited a masterful ability to negotiate difficult political scenarios.  The most telling example of this was his navigation of the draft.  Clinton received his draft notice towards the end of his first year at Oxford, where he was studying as a Rhodes Scholar.  He was adamantly against the war, but he always maintained a moderate disposition towards the anti-war movement.  Despite his convictions against the war, Clinton fundamentally believed in the system.

But his friends knew that he had invested too much time, hope, and ambition in his political future to abandon it by resisting. “Maintaining viability within the system was very important to him. Right from the start we all took his aspirations with real proper seriousness,”

He always believed that his best work would be from within the system, not from without.  His actions to avoid the draft, therefore, remained in line with his calling to lead a political life and lead from within the existing system.

There’s something our generation can learn from this.  So many of us are fed up with the political system as it is, and justifiably so.  We turn to business, or non-profits, or NGOs as we seek ways to make a difference.  In doing so, we leave a broken system unattended.  If the best among us abandon government, who then will lead?


Above all, Clinton was a conflicted person.  His life seemed full of contradictions.  Maraniss puts it best:

Then and always, these contradictions co-existed in Clinton—considerate and calculating, easygoing and ambitious, mediator and predator.

We have to consider Clinton in the context of his great ambition, his incredible political skill, and his very human weaknesses.  I think he recognized early where he wanted to go and where his skills might best be used.  After reading this book, I have little doubt that his intention to become President was rooted in a desire to do something good when he got there.  I’m inclined to respect that.

In a particularly memorable speech at the 1980 DNC, Clinton warned that the political and economic systems of his day were breaking down:

We have seen high inflation, high unemployment, large government deficits, the loss of our competitive edge. In response to these developments, a dangerous and growing number of people are simply opting out of our system. Another dangerous and growing number are opting for special interest and single interest group politics, which threatens to take every last drop of blood out of our political system.

Inflation notwithstanding, that sounds awfully familiar, doesn’t it.

Why you should vote tomorrow, even if you live in California

Since recently becoming a citizen, how I follow politics has changed.  Not being able to vote allows you to examine the political debate in a detached way.  You can argue both sides, make abstractions, and never have to worry about making a choice.  It’s nice, actually.  From the sidelines, you can see more clearly the mad and infuriating genius of the American political system.

But as a citizen, the fantasy evaporates.  When we elect someone, we choose them over another.  We decide that one candidate is more deserving of an elected position than their opponent.  Making the choice can be difficult, particularly at a time when combative rhetoric and absurd amounts of money smother most real conversation about issues and principles.  There is much to be concerned with in how we elect our leaders, but our votes are important nonetheless.

That’s my thesis, at least, but not everyone agrees.  NPR ran an article this week about the “Other Abstinence Movement” — non-voters.  Many of the reasons given by non-voters for their abstinence draw on religious or cultural motivations for not voting, such as a Native American not voting as an assertion of their tribal sovereignty, for example.  These I can understand, but they apply to only a small proportion of the ~ 45% of American’s who don’t vote.  Let’s take a look at some of the other reasons given in the article, which I hear all the time.

“I do not vote because I believe that at the end of the day, money is more powerful than a ballot.”

Without question, money has become an enormously powerful force in politics.  According to the NYTimes, the Obama campaign has raised $934m while the Romney campaign has raised $882m.  That’s almost $2b dollars spent on the presidential election alone.  The Center for Responsive Politics estimates another $4b will go towards other elections, bring the total to nearly $6b.  For some perspective, that’s enough to build about 1000 elementary schools; for more perspective, that’s only enough to pay off less than 1% of next years projected budget deficit.

But that doesn’t mean you shouldn’t vote.  In fact, it implores you to vote.  Money may influence politicians, pay for TV adds, or lobby for special interests, but as long as people vote, as long as citizens do their best to choose the candidate they think will be the best president (or congressman, or city council member), we might still have our say.  Only when we stop voting has money won.

“A simple understanding of statistics shows that my vote does not matter.”

It’s easy to suggest that a vote doesn’t matter.  There are 300 million people in this country, so at that level, yes, one vote is unlikely to make a difference.  And that’s not to mention the electoral college, which does more to disenfranchise American voters than any voter suppression measures.

But that doesn’t mean you shouldn’t vote.  If the 2000 election teaches us anything, it’s that elections can come down to individual votes.  Moreover, the broken electoral college system is thrown into sharp relief in close elections, especially when the popular vote and the electoral college don’t align.  In those cases, your Republican vote in California or your Democratic vote in Texas do matter, because they expose our system’s flaws.

Your vote matters, for your country and, most importantly, for you.  It takes the concern of ordinary citizens to make change.  High speeches and promises by politicians won’t do it, we have to get involved.  Voting is the first, most basic, and most important measure of involvement.  So go vote tomorrow, even if you live in California.  Go now and vote.

The Educator’s Dilemma: Three questions on technology and education

There are always people talking at Oxford.  You could make it your full time mission to hear all the interesting talks and still miss more than you catch.  I thought it would be valuable, both for myself and whomever finds time to read this, to share my impressions from these talks.  Views and opinions here will be my own, and don’t necessarily reflect the presenter’s point of view.

The following is my response to a lecture entitled “Personalization, Backpacks Full of Cash, and Rockstar Teachers: The Intersection of Technology, Free-Market Ideology, and Media Hype in U.S. Education Reform.”  It was presented at the Oxford Internet Institute by Justin Reich, Phd, Fellow at Harvard’s Berkman Center for Internet and Society and Founder of EduTechTeacher.

The Educator’s Dilemma:  Three questions on technology and education

1) Is education delivered or emergent?

The education system in the United States is broken; there seems to be little argument here.  What people do argue about, however, is what to do about it.  We’re forced to ask fundamental questions about what education is and what it should be.  Should education aim to produced informed citizens?  Workers for the labor force?  Critical minds?  Can it do all three?  Should the education system produce anything, or is that a fundamental misconception in itself?

Reich briefly discussed two schools of thought in U.S. education policy, formed around two early education theorists, Edward Thorndike and John Dewey.  Thorndike believed in “education as the science of delivery”; Dewey conceived of “education as life” (Reich).  Thorndike’s vision won the day, and our education system today largely incorporates his conception of learning.  Young minds are empty containers to be filled with facts.

Dewey’s vision for education hasn’t been forgotten though.  Reich remarked that educators in the U.S. dream in Dewey and live in Thorndike.  As we are forced to reimagine education in the U.S., I think the question deserves another look, particularly as technology offers new ways of educating.  Do we believe that education is delivered?  That students are to be taught in an industrial, assembly-line manner?  Or do we believe that education emerges through experience and discovery?  How we collectively answer this question will inform our policy decisions.

2) Where does technology fit in?

There are countless passionate and intelligent people working to fix education; this is the one glimmer of hope for a broken system.  These teachers, administrators, policy-makers, activists, are increasingly joined by technologists and investors.  Technology is not a silver bullet.  iPads do not equal education reform.  But I think it’s unequivocally positive that some of the talent and capital of the technology sector are focusing on education.  The question is how can technology help?  Where does it fit in?

Reich made an important distinction between technology that transforms how we educate and technology that puts a shiny veneer on an old, failing model.  He’s right to suggest that improvements at the margin won’t be enough to make an impact.  However, another example Reich gives illustrates a problem that technology encounters in entrenched systems like education.

We point to Wikipedia as an example of the marvels of peer production.  It is just that, but we forget about the online encyclopedias that failed.  Why did Wikipedia succeed where others fail?  Reich suggests (based on a forthcoming paper by his colleagues), that Wikipedia succeeded because it developed an innovative process around an established product.  Other attempts failed because they made no process improvements or tried to develop an innovative product that was incompatible with users’ entrenched expectations about encyclopedias.  When people expect things to work a certain way, it’s hard to disrupt their habits with technology.  Education faces a similar barrier, where norms and expectations of how education should be conducted are so deeply ingrained, particularly in parents.  This could prove an obstacle for real technology-driven innovation in education.

One answer may exist in systems like Khan Academy, which preserves traditional teaching practices (like lectures and tests) but reimagines delivery methods (by enabling personalization of lessons).  Here again we encounter the delivery vs emergence debate, but as I’ll discuss later, I think there’s a middle ground.

3) How do we test and implement new technologies for education?

Product development requires an iterative process of release, review, and improvement.  Startups are told to build a “minimum viable product,” get it in the hands of real users, see what works and what doesn’t, and rebuild or pivot as necessary.  This model can be effective for building quality products quickly , and education would benefit from adopting it.  However, any iterative process anticipates and accepts failure.  While this failure may be celebrated in the context of product development, it becomes a problem in education.

When six online encyclopedias fail and one succeeds, we say the market functioned as it should.  We value Wikipedia and are generally no worse for the failure of the others.  In education, those failures affect the development of children.  Failure, a necessary component of developing a quality product, can’t be accepted and celebrated in the same way.  The response may be that the system fails certain children so badly and predictably, as indicated by zip code, race, socioeconomic status, etc, that we might as well try something else.  It seems unethical, though, to experiment with new practices on an already underserved population just because the status quo is so inadequate.

Where do we go from here?

First, passionate and intelligent people need to keep trying.  Technology won’t solve anything on it’s own, but introducing new people and ideas to the education debate can’t hurt.  In that spirit, I’d like to make a suggestion.

Let’s start with a perspective that views technology as a supplement, not a replacement to classroom interaction and teacher engagement.  For core curricula, particularly in math and science, a system like the Khan Academy can deliver lectures and assessments.  Teachers, therefore, are free to work more intensively with students that need it, either for remediation or advanced work.

The model then becomes a hybrid of the delivery and emergence philosophies.  Students receive instruction in a standardized form but are able to progress through the material at their own pace.  As we learn more about how students use the system, we can develop mechanisms for allowing them to chose topics that they find most engaging.  They learn by exploration as well as delivery.

For implementation, we direct a fraction of education budgets to funding small pilot programs.  The programs should be small and targeted particularly to those most in need of improved education programs.  However, the programs should be an option, something parents and children could opt-in to.  Funding should be available to ensure that economic factors don’t impede children from enrolling.  That would likely mean transportation assistance and potentially after school programs, as the pilot programs may be located at a greater distance from home than local schools.  By making the programs voluntary and free, we might mitigate as much as possible the complex ethical questions discussed earlier.

These are meant as humble suggestions.  I suspect that programs like this probably exist already, in some form or another, and that things are always more complicated than they appear from the outside.  But the more fresh perspectives we can bring to the education discussion, the better off I think we’ll all be.

I’d also like to point out a serious gap in using technology to educate in the humanities and arts.  Despite the dire need for scientists and engineers, to forsake english, history, theology, philosophy, music and all the wonders of the humanities would be a travesty.  We need people who can think, who can act as citizens of the world and approach questions of science and nature from an informed and ethical position.  These things cannot be achieved in math and science alone.

The most hopeful thing that Reich presented was a single number: 15,000.  There are about 15,000 school districts in the United States.  If we can supply these districts with the framework, technology, and funding to innovate as they see fit, we can make this work.  We have to.