Deep Learning in Training (Part 1)

Part 1: Deep Learning vs Flat Learning

When at school, how often were you presented with information that meant nothing to you?

Perhaps it had no bearing on what you were interested in or no association to what you already knew. Teachers ‘drilled’ information into you by making you recite parrot fashion until you had a useless list of data installed!

Did you ever sit in lessons thinking ‘why?’ and ‘what’s this got to do with me’ and ‘gee, this is boring’? I remember thinking that a lot at school. As a geography teacher talked at us about the major glove manufacturers of Manchester, my brain would drift elsewhere to ‘Dungeons and Dragons’ and ZX Spectrum computer games and girls (forgive me, I went to an all-boys school, and girls were a mystery to me!) To misquote Lewis Carrol, I believe they were called ‘lessons’ because my interest in them would lesson and lesson.

Welcome to the world of ‘flat learning’… data coming at you from an external source… bearing no relationship to your interests or your real-world experiences.

What if the geography teacher had started with our existing, albeit limited, knowledge and experience of gloves? Perhaps by asking us some questions like: How many of you have at least one pair of gloves? What sort of gloves do you have? What are they made of? Do you know where they come from? Better still, the teacher could have asked us (in the previous lesson) to bring a pair of gloves with us. Then we could have examined our gloves, looked at the labels and see where they were made. Now we have some sort of connection to the content of the lesson.

This style of teaching would help to create ‘deep learning’… starting with the audience’s experience and working out from there to new information.

‘Flat learning’ is hit and miss; it can only be engaging by fortuitous accident. Information streams from the presenter and it may or may not link to the knowledge and experiences of the audience. To use a metaphor, often quoted in NLP, “everyone has their own unique map of the world”; flat learning can sometimes land… but more often information is lost at sea. ‘Deep learning’ starts with the map, the shared experiences of the group, and helps to develop new pathways to previously uncharted territories.

By modelling the behaviours of people that truly engage their audience, we developed the Deep Learning model. Here we have our first rule of the ‘Imaginarium Deep engagement approach to Learning’ (IDeaL):

IDeaL Rule #1   Start with the mind of the audience and work from there!

In part 2, we will explore Deep Learning AI and the Brain…

By Joe Cheal

joe@imaginariumdev.com

www.imaginariumdev.com

The Model Presenter by Joe Cheal and Melody Cheal

For lots more information on how to engage your audience, see The Model Presenter. To order your copy click here.