Each year at the renowned EDUCAUSE Learning Initiative Conference, a global coalition of educational technology leaders at the NMC and ELI unveils a pithy, expertly curated report on disruption, innovation, and the controversial future of higher education.
Known as the Horizon Report, the initiative “charts the landscape of emerging technologies for teaching, learning, research, creative inquiry, and information management” (⎋). This year’s release, fittingly unveiled in The Mile High City, is pivotal: it’s the first to leverage a full decade of publication history in its projections. But more importantly, it coincides with what a compelling majority of news media, academic institutions, and Silicon Valley frontrunners are calling “the year of disruptive education.” To the excitement of those who attended the unveiling a few days ago, the 2013 Horizon Report lives up to these momentous expectations. Of course it bears its share of shortcomings, but on most counts, it offers a strong survey and forecast of emergent trends in educational technology.
In this article, I’ll explore a selection of the more intriguing and impactful assertions in the Horizon Report. Drawing on themes from the Learning Initiative Conference, I’ll substantiate, challenge, and extend some of the report’s assumptions around learning analytics, MOOCs, gamification, wearables, and other technologies. This post will grow over time as new analyses are published. It will also evolve to reflect inbound reader feedback: email firstname.lastname@example.org to contribute your data, commentaries, or other expertise.
Assertion: Personalized learning is undersupported.
“The demand for personalized learning is not adequately supported by current technology or practices. The biggest barrier to personalized learning is that scientific, data-driven approaches to effectively facilitate personalization have only recently begun to emerge.”
Verdict: Absolutely, but that’s not the whole story.
Demand for personalized, individualized, adaptive, and otherwise “customized” learning experiences has surged in recent years. This trend flows from rising expectations about customizability in almost every other industry: entertainment, online content, games, medicine, communication, transportation, etc. As relevant business models gain traction and technologies improve, consumers — à la students — anticipate ultrapersonalization in most facets of daily life. Because education lags decades behind in this respect, the void is especially pronounced, provoking greater insistence.
Even as consumers expect personalization, it is only expectation, not action, that drives the trend. For example: to a content entrepreneur or application developer, it seems absurd that auto-personalization would rely on deliberate customer action. With the exception of self-identification for new users, the conventional expectation is that products adapt based on data collected organically and on the fly. No user should have to purposefully or repetitively report how, when, where, or why they might need, want, or benefit from certain flavors of customization. After all, that would be obtrusive, intrusive, and inelegant. But pedagogy isn’t the same thing as OTT VoD or SaaS.
For its part, the Horizon Report ascribes higher ed’s shortcomings in personalization to the nascency of learning analytics. Yes, this is a solid and much-needed assertion. Learning analytics are the most accurate, advanced, and scalable springboard for personalized learning today, but they’re still in the alpha stage (⎋). However, the report doesn’t recognize these consumer expectations as bases for increased demand in the first place. Its assumptions somewhat overlook education’s “third rail” of consumer behavior — rather, student participation — in shaping forthcoming implementations and evolutions. Unique to education, student cooperation in driving personalized learning will be critical to successful, large-scale implementations of personalization in the earliest phases.
What’s more: learning analytics are one thing, but the systems needed to deploy the results of those techniques are equally essential, and even more lacking. As analysts squeeze every conclusive ounce from oceans of data and try to systematize their approach, educational technologists and engineers still need to figure out how they’ll act on these conclusions once available. Their task isn’t merely mathematical; it’s pedagogical, philosophical, and even physical. Though it’s sometimes compared to Paul DePodesta’s work in baseball statistics, the scale, intricacy and import of the task make it leagues more difficult. It hinges on making the impractical, practical.
All told, these considerations are probably greater “barriers to personalized learning” than the incipience of data science. For the field to emerge successfully within the report’s projected three-year timeframe, we’ll have to address these issues in just half that time. On the other hand, the Horizon Report is (1) justified in assuming data science is the key to personalization, and (2) judicious in identifying demand as a primary concern in personalized learning today. To reiterate the verdict: absolutely, but that’s not the whole story.
Assertion: Tablets should be treated as a technology unto their own.
“The tablet has come to be viewed as a new technology in its own right, one that blends features of laptops, smartphones, and earlier computers with always-connected Internet and thousands of apps. It has become even clearer that they are independent and distinct… Not a new kind of lightweight laptop, but rather a completely new technology.”
Verdict: Perhaps, but that’s a slippery slope.
To the extent this viewpoint holds true, it’s a byproduct of legitimate free-market trends muddied with distinction bias and availability cascades. Though very distinct from academia, the interface design industry, for example, has tried to actively overcome the idea that tablets must be treated as a technology unto their own. As represented by widely-accepted best practices in that industry, conceptually fragmenting new technologies in their own classes can be an indication of poor systems understanding more so than merit.
That’s not to say the viewpoint isn’t useful. Not only does the uniqueness of tablet hardware force educational technologists to reconsider their differences, but popular usage paradigms outside of the university suggest that students view tablets differently from other devices and content-oriented media. This provides a rare, mass-psychological opportunity to instructional technologists to take advantage of this trend in bringing greater respect and focus to educational tools.
Likewise, it’s also true that tablet software ecosystems are radically different from those surrounding other computing technologies in education. Opening the door for greater democracy, competitive pricing, and interdisciplinary material is one huge emerging benefit of the so-called “tablet revolution” in higher education.
Nevertheless, the Horizon Report’s text doesn’t feel so much “descriptive” of these phenomena as “assertive” of their merits. There’s great danger in this line of thought because it may over-encourage instructional designers and technologists to treat the tablet as if it cannot accommodate those standards-substantiated learning modalities which are appropriate for many users. Similarly, in special-needs higher education and education for low-income students, tablets often simply cannot be treated as a separate class of technology, but rather as the only viable learner-level technological tool. In these cases, the devices must fulfill the roles of many paradigms — though they are capable of this, it could be a disservice to the student and teacher to regard them as “instructionally unique” when they are simply compensating for alternatives.
On the whole, tablets present a vibrant array of instructional and technological opportunities, but to regard them as entirely “distinct” and “completely new” may be to overlook the traditional modalities they can also support, even while maintaing an economic edge. So can tablets be treated as a technology unto their own? Perhaps, but it’s a slippery slope.
Assertion: 3D printing will be essential to ed tech within five years.
“3D printing is already pervasive in a number of fields… Over the next four to five years, 3D printers will be increasingly used in the arts, design, manufacturing, and the sciences to create 3D models that illustrate direly complex concepts or illuminate critical ideas, designs, and even chemical and organic molecules.”
Verdict: Hopefully, but be skeptical.
Also called rapid prototyping (industrial design) or additive manufacturing (engineering), 3D printing is the oddest selection covered in the Horizon Report. Aided by modeling techniques like CAD and CAT, 3D printers construct layered, tangible prototypes of structures described to them as matricies of three-space data. Like all printers, they use a sort of “ink”, face issues with “resolution”, and accommodate different scales of projects.The technology has largely been popularized by MakerBot Industries as “Replicators.”
But even as consumers have been able have small 3D printers in their homes — or print to their commercial counterparts remotely — for several years, the 3D printer doesn’t seem to have revolutionized productivity in either homes or school like the 2D printer did in a fraction of the time. Part of the issue may be the lack of affordable 3D scanning… a natural, even essential, companion technology.
Furthermore, as most educational technologies tend towards digitization, abstraction and simplification,3D printers run in exactly the opposite direction. It isn’t that their potential or value is questionable; after all, the possibilities for science and engineering education are almost endless. Rather, their compatibility with current trends is very limited.
To some extent, the Horizon Report has a history of wild inaccuracy where it comes to one of the two annual long-term-horizon predictions. This seems to hold when the technology in question is generally “strange” or where there’s little student-level advocacy involved. In the case of 3D printers, by and large, both are applicable. To quote the report: “Simply capitalizing on new technology may not be enough; the new models must use these tools and services to engage students on a deeper level.” In sum? Be hopeful, but skeptical.
Assertion: MOOCs don’t push the boundaries of pedagogy.
“Although there are clear differences among the major MOOC projects, it is important to note that their basic pedagogical approaches are very similar.While quality of the video and related content provided is high, the delivery model is very much based in traditional models of instruction, and does not include the notions of openness and connectivism outlined by Siemens and Downes.”
Verdict: Exactly, and they direly need to.
Now that 80% of people believe college isn’t worth the money, higher education has to face the needs of students as consumers. Following last fall’s enrollment season, the media has started to pay attention, too. Massive Open Online Courses, or MOOCs, may never supersede the higher education paradigm, but they will inform one another in parallel as the first grapples with revenue and the latter with relevancy. As referenced by the New York Times in an article on MOOCs: there’s a tsunami coming.
But is there? While MOOCs are absolutely disrupting the “business models” of higher education, it is increasingly clear that MOOC providers are less interested in challenging enlightenment-era notions of one-to-many lectures and curricular gradation. MOOC providers like Coursera, Udacity, and edX have many an unprecedented opportunity to overturn classical pedagogies in favor of connectivist and authentic eLearning experiences, modularized delivery, and personalized assessment. The technologies in play are perfect for these paradigms… so why aren’t they in motion?
For all startups, risk plays a large part in determining courses of action. While each of the major providers is clearly more progressive than standalone brick-and-mortar institutions, their business plans, investors, and development roadmaps may have them feeling “worked into a corner” with respect to pedagogical experimentation. In this vein, their models are all very similar. MOOCs simply aren’t pushing the boundaries of pedagogy… and they direly need to. ₪
Edit: I cover MOOCs much more thoroughly in my article “The Road to Better MOOCs”.