Climbing out of the Trough of Disillusionment: Making Sense of the Educational Data Hype Cycle

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