Think of a time when someone told you details about something you just didn’t care about — full TMI. When this happens, unless you completely tune out, it can feel like getting hit on your head with a brick. Now recall someone speaking in a foreign language. You heard sounds but could not grasp the meaning.
These examples illustrate an old-school style of training. It used to be common for teachers to present information regardless of whether students cared about it or had the cognitive building blocks to understand it. We like to think this approach has been tossed in the trash bin of history but this is how most corporate LMSs are used, even today. It’s how most were designed.
However, there is a shift happening. Corporate training and L&D both are embracing the science of learning. New training systems that embrace and leverage the science are hitting the market at a brisk pace and the old guard are scrambling to augment their offerings.
Part of the scramble is to add artificial intelligence (AI) to the learning mix, mostly addressed to course assignment. Is the problem with this obvious or am I missing something? Use of AI in this way is just a fancy way of jamming down yet another assignment. On the other hand, it can offer a tremendous improvement in the compliance domain. It could (if regulatory bodies accept it) enable us to tightly tailor atomized courseware based on what users know and don’t know.
So, good news and bad news. In the examples above, AI addresses the foreign language problem, but outside of strict compliance training scenarios, it still misses the motivated, active-learning aspect. So will this mean we can soon expect bots to start hitting us with TMI bricks?
There is a better way, a way where humans decide.
We construct our knowledge. We build new knowledge with the knowledge we already possess. And as our knowledge grows, it becomes more uniquely our own, reflecting our experiences and beliefs. In this way, learning is a process of constructing meaning and knowledge systems. The more we learn, the more we can learn.
Many believe that we learn most effectively through active learning. Learners acquire knowledge most quickly and effectively through experience, by actively engaging in the world. And for some learning theorists, the pinnacle of learning efficacy comes via active collaboration with others.
According to social constructivists, the process of sharing individual perspectives — called collaborative elaboration — results in learners constructing understanding together that wouldn't be possible alone. (Wikipedia)
But learning also benefits from relevant context. We most firmly grasp what we learn in the flow of life. And this aspect also helps spur cognitive motivation. As the TMI example illustrates, learning requires an active mind eager to learn.
Embedding learners in a relevant situation that requires learning will motivate their minds. Enabling their engagement with the minds of their peers will boost their understanding. And if we also add an iterative approach — apply knowledge, compare, apply — then we’ve really got something.
If you’ve read any of our previous posts, you probably guessed that these principles are the guiding framework for what we call a social learning sandbox (SLS).
Now consider an example. Below is a rough outline for the design of an advertising copywriting SLS. A manager wants her team to develop copywriting skills while actually producing workable output.
Step 1: Present the challenge by stating, “Create an ad for our product using 300 words or less. We will use the entry the group indicates is best.”
Step 2: Assign guiding resources (courses, webpages, videos, etc.).
Step 3: Assign a checklist that requires defining the customer.
Ask, “What benefit do prospective customers seek?” Use multiple choice and ask for first, second, and third choices. For each selection, ask “Why?”
Ask, “What objections limit their range of considerations?” Use multiple choice and ask for first, second, and third choices. For each selection, ask “Why?”
Ask, “What is their personality type?” Present guiding resource information such as Myers-Briggs categorization of personality types. Use multiple choice and ask for choice of primary and secondary types.
Ask, “What ad appeal seems best?” Present guiding resource information. Use multiple choice and ask for choice of primary and secondary choices.
Step 4: Present all draft checklists for all participants to view.
Step 5: Assign the customer definition checklist again.
Step 6: Present all final checklists for all participants to view.
Step 7: Assign a checklist requiring a written draft.
Step 8: Present all drafts for all participants to view.
Step 9: Assign a checklist requiring the final written entry.
Step 10: Assign a checklist that presents all entries alongside their corresponding customer definitions for all participants to view. State, “You’re now the manager. Pick the best ad. Pick the best customer definition. Explain why.”
Step 11: Assign a checklist that presents all checklist responses from Step 10. State, “You’re now the CEO. Which manager should be promoted?”