Monday, 26 August 2019

Working on the #LearningEngine matching #learning to #skillgaps #skills


Forget the search engine, ravel on the emergence of the Learning Engine (admittedly it is still a dream in progress, but we are getting closer)

What made search engines so innovative decades ago? 
They created connections. Connections between online users and content. The search engine developers did not produce a lot of content, but they referred to content from outside providers, and that was what made it special: the immediate connection. It connected supply with demand, connecting small and big businesses, individuals and groups. The service built upon existing new developments that each of the content producers provided. 
Content free and available. A great big benefit of the content that comes up in the search engines is of course that it is free, ... which is a lot more difficult if you are trying to build a learning engine. Professional courses are rarely free (MOOCs notwithstanding), and in a lot of cases even the courses themselves are behind closed walls: e.g. online courses only available for employees, for registered students...

Search engines are great, but Learning Engines are becoming a really urgent demand
The shift in our professional society is no longer about jobs that disappear due to automation, it is about jobs diversifying through the demands of change, driven by innovation. Learning to learn is becoming essential to being employed and moving forward (or at least it seems that way for some of the jobs in sectors driven by innovation and change). 
In order to learn how to do a variety of jobs, we need to learn, and we need to personalize each of our learning journeys based on our previous experiences and skills, both hard and soft skills. This is where the Learning Engine comes in and takes shape. At InnoEnergy I am now co-developing learning for real life jobs. At present ‘addressing the skills gap’ is all the rave. LinkedIn is investing in its Economic Graph, Burning glass and alike are gathering data on Skills, countries and regions are building skills taxonomies (e.g. Nesta ), that can be used either in manual brainstorms and in Artificial Intelligence driven projects. 

If you take into considerations these latest tech-innovations and options, it isn't difficult to imagine a true personalized Learning Engine. 

The challenge is how to build a Futureproof Workforce? Maybe a Learning Engine
With the Learning Engine in my mind it combines innovation, AI and learning skills for the sustainable energy sector (as EIT InnoEnergy works within the sustainable energy sector). Basically, the project identifies industry needs, pinpoints emerging skill gaps in the sustainable energy sector, analysis the existing workforce to know where urgent skills gaps are situated and then refers employees (or employee groups) to a personalized learning trajectory to alleviate their skills gap. 
The combination of these steps should ensure that the employees of the sustainable energy sector stay futureproof in a quickly changing working environment. 

This project helps to realize the emergence of the ‘Learning Engine’, an intelligent career-oriented engine which knows your own skills and signposts you to where you want to go with your career by suggesting a personalized learning track. 
Just imagine that you go to the Learning Engine and you simply type in “Director of Innovation’s in offshore wind energy” and the engine immediately returns a tailored, personalized learning track consisting of a variety of certified trainings from both universities, corporate academies, open educational energy resources and coaching options! Personally, I think that would be quite a catch!

Learners mix and match already
In a way, we already see this shift towards a more quilted professional learning in the MOOC’s which are taken by professional learners to enhance their career opportunities. Those career-minded employees register for MOOCs developed by universities as well as businesses, and they take a few courses here, and a few courses there. Soon employees will be able to link different course certificates to ensure a future-proof career (whether we should be using blockchain in Education to validate the learning trajectory is something else (see some mails on this here and here).

Corporate academies will need to open part of their courses: are they willing?
As the project evolves, it is clear that the AI engines are running and becoming smarter as additional data is fed into the system. But the main challenge is still: how to get access to course descriptions so we can signpost learners to those courses. If we don't have access to courses, even descriptions than we cannot send learners to them. 
I would think that corporate academies would benefit from sharing some of their courses: if they form a network, they will no longer need to develop all the courses, they could 'swap' or agree to develop specific courses and find other courses for their employees at competing companies. Because although they are competing, all of them have basic courses for their employees, and those course costs could be cut by coming to a course-development agreement.