Roughly two years ago, I was attending an education conference and more than a few of the hallway conversations overheard had to do with the disruption that adaptive learning would drive in higher education. Stories of companies that could provide dynamically generated content to the exact learning needs and difficulty levels of learners filled the air as venture capitalists swooned over the anticipated massive changes in higher education.
Fast forward to today, and while adaptive learning has created a small foothold in higher education, its adoption has not (as of yet) lived up to its lofty expectations. While I am optimistic this will change, I see a strong and more immediate opportunity in an adjacent market – corporate and professional training, particularly in segments such as IT training and also the many areas where one has to take standardized tests in order to work in a profession or maintain their licensure.
Higher Education hates black boxes – in fact the notion of faculty primacy in
the creation and development of content nearly demands that there must be transparency – however in many circumstances the underpinning logic and algorithms used in adaptive are difficult to communicate and even more challenging to alter. This has driven diminished adoption as prospective postsecondary clients struggle with what’s going on under the hood. In contrast, corporate and professional training providers are much more likely to accept there are sophisticated analytics working in the background provided the resulting educational experience drives efficacy in learning.
Adaptive also fits well with the consistency of content often found in corporate and professional training. Good examples include IT certifications (Microsoft, Citrix, etc.), initial licensure testing for real estate and insurance (consistent for all test takers in a given state), and even subjects areas as focused such as OSHA certifications. In each of these situations thousands (if not tens of thousands) of learners toil away on fixed body of content which allows adaptive engines to optimize and personalize learning experiences at a rapid rate. In contrast many university environments operate at a micro level where content is presented to a single class of students or at best several sections. However seldom is content uniform across institutions. This naturally dampens one of the key ingredients of efficient adaptive learning technology – the large statistically relevant sample sizes needed for the underlying algorithms to do their work.
Finally, ownership changes in corporate and professional
training should result in companies investing in their products to order to differentiate. In general, the third party companies who operate in this space are fragmented. In the past few years, private equity firms have been acquiring platform companies with the intent of rolling up some of the smaller players and building a competitive moat. (And this says nothing of the move by leading enterprise software players into corporate learning via HCM software acquisitions, such as Oracle’s deal for Taleo for $1.9bn or SuccessFactors’ for Plateau for $290mm). While there are several paths to this objective, adaptive learning fits nicely as a mechanism to differentiate – after all, companies that employ adaptive will need to be better capitalized (adaptive is more expensive to implement relative to static content) and will want to amortize these investments across multiple product lines and segments.
This is not to say that focusing attention on a different market is easy and it certainly won’t be without growing pains for the adaptive companies, but given the market opportunity it’s a logical evolutionary step. Over the coming months and years, I look forward to hearing stories of how adaptive players adapt!
Editors Note: This guest post is written by Niraj Kaji, who has worked for over a decade in Higher Education, including at Bridgepoint Education, Walden University and Laureate Education as well as an entrepreneur in founding four start-ups. All points presented represent the personal views of the author and in no way reflect the opinions of his current or past employers.