- Is the new behavior/information you are teaching truly useful? - not just to the organization, but the individual we are asking to change.
- If it is useful, how will the learner know? - are there some compelling case studies that can be used to demonstrate the impact?
- Is it easy to implement? - even if the benefit is clear, if using the new process/behavior/information is cumbersome, the change will not happen efficiently.
The science of learning: Thoughts from the experts
The first session I attended at ATD ICE after the Opening Session was a panel on the Science of Learning. The panel was facilitated by Justin Brusino (@atdSciLearn, @atdLearnTech) and included Sebastian Bailey @DrSebBailey), Julie Dirksen (@usablelearning), Karl Kapp (@kkapp), Alice Kim (@AliceSNKim), and Art Kohn. First of all, great panel format. Each speaker had a chance to talk about a certain topic and had plenty of time left for Q&A at the end. I don't care much about the panels that have only Q&A, because it is hard to keep track of a consistent thread. This way, we got some really cool information, which inspired deeper follow up questions. Kudos to Justin Brusino for putting it together. The topics were all around the way our brain receives, stores, and recalls information; the forgetting curve; and, more importantly tips on how to account for brain science when designing learning. Let's look at some of the topics shared. Julie Dirksen tells us that "paying attention" is the brain's way of allocating resources. We learn and retain information based on the reward principle. If the reward is abstract or too far into the future, our brain doesn't feel it wise to allocate immediate resources in order to achieve this reward. For learning, the natural reward is using/applying the information learned. From a design perspective, then, we need to teach what we need to use when we need to use it. "Just in time learning," but also useful. With this in mind, ask some questions when designing learning:
There is much more to learn.
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