Measure, Match and Mobilize: Rethinking Learning in the Digital Age

Digitization is both a challenge and part of the solution for lifelong learning. When we discuss its impact, we often focus on two questions: what and how we will (have to) learn in the future. Going beyond that I would like to draw attention to how these new technologies change our education system as a whole. This systemic impact of digitalization on lifelong learning can be illustrated in four theses and shows that digitization offers a fix for what it damaged before.

First, let us start with a piece of honesty: our traditional degrees are pretty broken. The speed of the digital transformation is a huge challenge for our education system since it leads to an ever-decreasing half-life of its main product – knowledge. Instead of pre-structured and broad curricula which last a lifetime, we need more flexible, modular and specialized learning for tomorrow’s challenges. Unfortunately, today’s degrees don’t meet these requirements. While learners invest more and more money and time to get prestigious diplomas, employers find that a degree or the institution awarding it have less and less predictive power regarding an employee’s future professional success. The result: traditional degrees are losing their signaling function. This is further enhanced by our growing mobility: when you can learn and work anywhere in the world, transferring your educational achievements across companies and nations becomes a necessity. Our current degrees offer neither the flexibility, nor the signaling power, nor the transferability required by digital societies.

Which is why, second, skills will replace degrees in the long run. This process has already begun: recent studies show that more than three quarters of employers think informal learning is very important, while only a good half of them would say the same of a formal education. It is no longer as important which university taught you to program or to interact – or if it was any university at all – as long as you can write code or lead a diverse team. The problem with informally acquired skills, however, is their invisibility: right now, we’re lacking the tools to measure and make transparent each individual’s skills adequately. Without this signaling function, without making the invisible visible and the informal formal, any new approach remains useless: We need to make sure skills can be communicated in a transparent, trustworthy way in order to fully exploit their potential.

Third, digitalization enables us to do exactly that: to measure, match and mobilize skills. Thanks to digitalization, we now have the technology at our fingertips to reliably and efficiently measure individual skillsets as they are developed; we can certify actual learning outcomes and competencies instead of relying on the learning path as a proxy. From outside the education system it has always been hard to understand why we measured more how many hours somebody spent in class rather than what he could achieve. Once we know what a person can actually do, we can match – again using technology – their skills’ profile to the requirements of any given job. This helps us find the best person for a job and the best job for each person – and is a valuable proof of whether our skills’ measurement was an adequate one. If the now visible competencies have a meaning for the job market, (digitally administered) skill passports will serve as the next generation of degrees, giving skills the signaling function they were lacking for so long. Matched against a common terminology – e.g. the European Commission’s ESCO as a first attempt – this will not only improve and speed up the matching process but also offer customized training opportunities for each individual – thereby truly mobilizing potential.

Digitization therefore offers a fix for a system that it helped to break before. But its impact, and that is my fourth and last point, goes beyond that. Thanks to market analytics, analyzing millions of job profiles and resumes every day, we can predict a shift in skills and skill requirements in real time. No longer will governments and education institutions have to rely on incomplete and old statistical data. With that kind of demand data, we now have the means to measure competencies against a current skill set. And training providers can customize their trainings to actual demands, while governments could use that analytic power to proactively meet future workforce developments by creating long-term education strategies.

We should see digitization not only as a challenge that will disrupt the process of learning but also as a way to a solution that will benefit lifelong learning as a whole. If we use digital tools to measure, match and mobilize individual skills and analyze the skill market, we can build a better system of lifelong learning.

The article has been published on WISE ed.review.



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