Deep Learning in Training (Part 3)

Part 3: An Example of Deep Learning

Have you ever sat in an audience where the trainer/presenter talks… and talks… and talks? How long can you hold your attention on the speaker or the content? Have you found yourself using strategies, like taking notes or doodling in order to stay present in the room?

Some topics will be right up your street, perhaps answering a question or solving a problem that you have. Alternatively, it may be pertinent to your day to day work or perhaps tingle bells of fascination! However, many topics, when taught in a traditional ‘talk and chalk’ approach are dry, featureless and barren; tumbleweed becomes your only friend. Welcome to the desert of ‘flat learning’.

When I’m running ‘Train the Trainer’ courses, I often get asked: “How do I make technical information or policy training interesting?” The assumption here is that we cannot run a technical/policy training session without dumping information on people. So, how can we take a dry subject and apply ‘deep learning’ to make it engaging?

Now, I don’t teach ‘Ladder Safety Training’, but imagine the following two scenarios:

  • The trainer shows a PowerPoint slide. It has ten things you need to do when using a ladder. The trainer starts with the first point and talks through it… and continues by discussing each point in turn.
  • The trainer asks the audience to imagine a ladder against a wall… and then gets them into small groups to come up with ten things that could go wrong if someone tries to climb the ladder. The small groups discuss and then the trainer asks them for ideas, perhaps writing them on a flipchart. The trainer might add a couple of other dangers. Then the trainer asks them to come up with ideas for preventing or resolving the things that could go wrong. Back into small groups to discuss and then the trainer asks them for the audience’s ‘top tips’. Now the trainer shows the PowerPoint slide and checks off the things already covered by the audience, pausing only to add any items that the audience may have missed (including correcting some problematic answers!)

The first approach (flat learning) is probably the most common and easiest for the trainer to control. However, whilst the second approach (deep learning) may appear more complex, it is actually less effort for the trainer and much more engaging for the audience. It presupposes that the audience already has knowledge (and it acknowledges the knowledge!) and it allows the trainer to draw from the group, bringing knowledge to the surface. This means it is a group-shared learning process.

Where the audience lacks information, then give it to them. However, if they have any experience or knowledge of the topic, find ways to gather it from them and then build on it. This gives us our third rule of the Imaginarium Deep engagement approach to Learning (IDeaL):

IDeaL Rule #3   Start with the audience’s existing knowledge, draw it to the surface and then add any missing information.

In part 4, we will explore applications of Deep Learning in training…

By Joe Cheal

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.