customised learning
July 22, 2019

Customised Learning, do you personalise your training?

By Tony Boobier

Continuing our month focussed on educating others, let’s consider the growth of customised learning.

To share a perspective on this, I am delighted to welcome back guest blogger, Tony Boobier. Tony has shared with us before on topics as diverse as location analytics, no goals & AI’s impact on your working life.

In this post, Tony muses on the need to stop our one size fits all approach to education. As a blog focussed on Analytics, Insight & Leadership, it seems fitting to challenge ourselves about this dimension of personalisation too.

Different education for different folks?

We’re all different, right? So why should those who provide training and educational services think that we are all the same?

Some years ago, early in my career I watched a language teacher use multiple training techniques simultaneously in the classroom – audio, visual and tactile. Afterwards I asked her why, and what was the technique she was adopting.

She explained that it was a proprietary process called ‘Brain Friendly Learning’, which links “theoretical knowledge about the human brain with new attitudes towards teaching and learning and then to the development of new practical strategies”:

Welcome to Brain Friendly Learning

Current scientific studies demonstrate that effective linking of the different systems of the brain during the learning process improves the transfer of knowledge into long term memory. Brain-friendly learning techniques are designed to maximise this advantage. Brain-friendly learning and Brain-friendly publications offers a selection of materials and seminars which will assist teacher organisations, schools, companies and individuals to improve the effectiveness of their teaching/learning.

Pomme“, she said to her classroom. And not only did she show a picture of an apple on her board, but she handed out an apple to the classroom to touch and feel, a little like a sort of memory reinforcement I suppose.

In essence, she explained, our individual brains learn in different ways. Some like to listen to explanations; others like to see either the words or graphics on a board; yet others like to try it for themselves, maybe with some sort of an online demo that they can interact with. Usually, it’s not one approach or the other, but rather a combination of some or all of these. We might describe this as ‘customised learning’.

Better training of technical subjects

A little while later I wondered whether this approach might also be applicable to more technical subjects.

At that time I was working in the insurance sector, and I gave a presentation on why that very complex process of insurance was no more difficult than a bowl of fruit. In front of me I had a glass bowl with a banana, apple and orange.

The banana skin represented contractual obligation; the apple represented subrogation (which is the legal right of recovery), and the orange represented the need to peel back the orange skin to understand why certain results were being obtained – nowadays I suppose we would call that the analytical element.

Years later, I was stopped in the London Underground. “Weren’t you that guy with the bowl of fruit?” He asked. At least he remembered something.

On a similar vein, in the early days of what we now know as the Internet of Things, I successfully encouraged conference attendees to hold onto a length of golden string stretched across the room, to reinforce the message of connectivity with people that you’ve never met. It was a gimmick but one which seemed to work.

So what’s this got to do with learning about data and analytics? Perhaps the same principles apply. How we learn about this most important of topics depends on our own personal learning style. Some want to understand by looking at charts, others by listening to lecturers and others just want to try it out for themselves.

Can someone tell the IT sector?

It’s a message which perhaps hasn’t quite been adequately grasped by those tasked with knowledge transfer about the technology sector. At this time of year there are no end of conferences and events which discuss the importance and relevance of tech, but it’s increasingly difficult to differentiate between them.

For example, in Europe alone this summer there will be over 30 conference events focusing on the insurance sector alone, all pretty well regurgitating the same stuff, and many with the same speakers and messages. Wider afield and across all industries, in the US there are said to be 50k conference companies, with over half a million events per year, and attended by 120m people. 60% go more than once. The market is said to be worth $150 billion annually.

I guess most of them are still adopting a ‘chalk and talk’ approach. The best of them provide that ‘tactile’ element through vendor stands, for those attendees prepared to engage in discussion, at the risk of their being harassed by vendors.

Some are already arguing that the conference industry is overdue for a major overall, away from that rather well established approach, towards one which is more dynamic, user friendly and ‘experience driven’?

If data really is the ‘new oil’, and analytics is the way that value is extracted from that data, isn’t now the time to put more effort not only into better knowledge transfer but also in improving how we get our messages across at a personal level?

With AI in Education market projected to reach USD 10.38 Billion by 2026, growing at a CAGR of 45.12% from 2019 to 2026, isn’t customised learning the way of the future?

What could customised learning mean for your education project?

Thanks to Tony for this timely challenge. As a trainer & a lecturer it certainly challenged me to up my game. What about you?

Interestingly since receiving Tony’s guest blog post, on Sunday I heard a preacher apply the brain friendly learning approach. He both spoke about faith, shared a picture of a mustard tree & gave out tiny mustard seeds to the congregation. Using all 3 learning styles in combination is effective.

So, what could you do differently? If you have the challenge of communicating the best use of Analytics in your business, how could you use customised learning?