Last month we argued that analytics in higher education has entered a trough of disillusionment. We posited that this is actually a good thing for higher education, because it means bringing attention to the hype itself. It means that we are making progress towards true productivity and student success. We need to learn how to spot the hype before we can move beyond it and realize the true potential of educational data and learning analytics.
It is our hope that the ‘analytics angst’ that has accompanied increased data literacy will put pressure on vendors to reduce hyperbole in their marketing materials and encourage institutions to reset their expectations. A more realistic view of educational data will result in greater adoption, more successful implementations, and results that move the needle by positively impacting student success at scale.
The Latin word communitas refers to a collection of individuals who, motivated by a common goal, come together and act as one. Community is powerful.
Common approaches to college and university rankings can sometimes have the unfortunate effect of pitting institutions against each other in a battle for students and prestige. As the U.S. turns its attention to meeting the needs of 21st century students and 21st century labor demands, the power of traditional university ranking schemes is starting to erode.
Student success is not a zero-sum game. Rather than fostering competition, a commitment to student success encourages cooperation.
It has recently become very apparent to me that the value of the things that I own is increasingly elsewhere.
Let me provide two examples.
Several months ago, Intel announced that it was shutting down all support and service for its Basis line of watches. The announcement came in light of a safety recall of the Basis Peak. Shutting down its data service for Peak watches was meant to mitigate safety concerns, since the watch only really ‘works’ if accompanied by its cloud-based service. Intel also offered a full refund on the watches. This was absolutely the best thing that Intel could have done. By withdrawing all features from the watch itself, and offering a financial reward for its return, Intel made it so that the watch’s sole use value was as a thing to be returned.
The announcement was sad for me. I was an early adopter of the original Basis B1 watch. I have had mine since before the acquisition of Basis by Intel in 2014. When other wearables from Fitbit and Jawbone (I have these first generation products in a drawer somewhere) were nothing more than step counters, the B1 also tracked heart rate and moisture levels. It was also a watch.
My B1 still ‘works.’ It is a reliable product, and I don’t worry about it exploding on my wrist. But in discontinuing service for the Peak, Intel discontinued serviced for Basis period. In other words, as of December 31, my Basis BI will lose all value. The watch itself will continue to function exactly as designed, but it will no longer ‘work.’ Sad though I may have been to hear that Basis was shutting down, my disappointment was eased when Intel offered me a full refund in exchange for my non-exploding watch.
I really like my (first generation) Automatic adapter. I like the accuracy with which it tracks my fuel economy and travel distances, and I like knowing that it would automatically notify a few key contacts in case of a collision. But the device has been less and less reliable recently. A recent email explained why:
Like the Basis watch, the value of the Automatic adapter lies, not in the adapter itself, but in the cloud-based services the company provides. Unlike Basis, though, what has left me with a useless piece of plastic is not the discontinuation of those services, but its reliance on a technology that has gone out of date. The device still ‘works,’ but despite firmware updates, it is not longer able to adapt to changing standards. My first generation adapter is now trash.
The major problem with this first generation adapter is that it relied heavily on two kinds of external service, only one of which the company had control over. There is the cloud-based analytics service (similar to that provided by Intel to support its watch), but the device also relied on a Bluetooth enabled smart phone for GPS (to track location) and SMS (in case of collision). Automatic has now learned their lesson. The most recent generations of their adapters do not rely on smartphones nearly to the same extent (if at all). But the fact that Automatic now has greater control over the device and the services that it makes possible does not change the fact that the value of its adapters lies squarely on the service side. The second the service piece is eliminated, the value of the adapter disappears entirely.
These are only two examples of many. I could also have mentioned Narrative, which produces a life-logging camera but whose service-based business model actually undermined product sales (because the camera only works if accompanied by a cloud-based service subscription. It is for this reason that the company recently closed down, only to be opened back up again as a result of an acquisition). And I could have mentioned the Apple Watch (which I love, by the way), which only has value if I resign myself to being locked in to the Apple ecosystem.
So things do not have value anymore. Just as the value of currency is no longer constrained by physical objects that even pretend to have some kind of innate value, so too have our devices ceased to have value in themselves. Our devices merely grant us access to information (and allow information access to us). And to be his extent, our things are not things at all. They are relations. Or, as Luciano Floridi would call them, they are ‘second-order technologies’ with the sole function of mediating the relationship of humans to other technologies.
In direct contradiction to Betteridge’s Law, we believe the answer is yes. Analytics in higher education is in the trough of disillusionment.
The trough of disillusionment refers to a specific stage of Gartner’s Hype Cycle. It is that moment when, after a rapid build up leading to a peak of inflated expectations, a technology’s failure to achieve all that was hoped for results in disillusionment. Those who might benefit from a tool perceive a gap between the hype and actual results. Some have rightly pointed out that not all technologies follow the hype cycle, but we believe that analytics in higher education has followed this pattern fairly closely.
In 2014, I wrote a blog post in which I claimed (along with others) that analytics had reached a ‘peak of inflated expectations.’ Is the use of analytics in higher education now entering what Gartner would call the ‘trough of disillusionment’?
In 2011, Long and Siemens famously argued that big data and analytics represented “the most dramatic factor shaping the future of higher education.” Since that time, the annual NMC Horizon Report has looked forward to the year 2016 as the year when we would see widespread adoption of learning analytics in higher education. But as 2016 comes to a close, the widespread adoption of learning analytics still lies on the distant horizon. Colleges and universities are still very much in their infancy when it comes to the effective use of educational data. In fact, poor implementations and uncertain ROI have led to what Kenneth C. Green has termed ‘angst about analytics.’
As a methodology, the Gartner Hype Cycle is not without criticism. Audrey Watters, for example, takes issue with the fact that it is proprietary and so ‘hidden from scrutiny.’ Any proprietary methodology is in fact difficult to take seriously as a methodology. It should also be noted that the methodology is also improperly named, as any methodology that assumes a particular outcome (i.e. that assumes that all technology adoption trends follow the same patters) is unworthy of the term. But as a heuristic or helpful model, it is helpful way of visualizing analytics adoption in higher education to date, and it offers some helpful language for describing the state of the field. Read more
Of these students, only 11% earn a bachelors degree in under 6 years. That’s compared to the rest of the population, which sees students graduate at a national rate of 55%. What this means is that 89% of first generation, low income students stop out, perpetuating a widespread pattern of socio-economic inequality.
Yesterday, I witnessed an exchange on Twitter that continues to bother me.
In the interest of citing sources and providing evidence, my first inclination is to embed the public conversation here. But, especially in this current climate, citing a personality in association with a controversial piece of content frequently serves to distract from the specific issues at hand. It is also not my intention to ‘call out’ any particular individual, but rather to use the situation as an opportunity to think through some issues related to philosophical charity, social media, and anti-intellectualism. Read more