The Act of Choosing Correctly Increases Transfer of Learning Through Reinforcement
Giving someone a chance to correct their mistake allows them to experience the impact and subsequent satisfaction of success, which strengthens retention and increases the chance of repeat successful performance. Unfortunately, some scenarios are not designed to allow learners to correct their choices—or, they’re ONLY designed to let the learner try over and over again without the benefit of learning from impact (see Part 2, Consequences) and reflection (see Part 3, Connections). If you have designed meaningful choices, allowed the learner to experience the consequence of their selected choice, and given them the opportunity to reflect upon its impact, then they are now ready to go back and try again.
Once the learner knows that they’re wrong or partially wrong, and they understand why, they’re ready to go back and try again. This should place them in a position to take a second look at the choices they’re offered and apply the learning they received from during the “consequence” and “connection” part of your design. After making their next choice, they’ll experience a new and different consequence. And hopefully, they’ll be right! When they are, your thoughtfully designed “consequence” will help them feel the impact of that choice and your well-designed “connection” will help them fully reflect about why it was the right thing to do. This successful pattern will be more permanently set in their mind, and more likely to actually occur in the real-world environment.
Endless Tries Can Minimize Effectiveness—Consider Incenting Precision
Although there isn’t a lot to be said about “how” to let the learner try again, there is quite a bit to be said about how to avoid letting their ability to try again minimize the effectiveness of what you’re trying to teach, or discourage them from trying their best to think critically. What I mean by that is that one of the biggest downfalls of the “try again” model is that it feels consequence-free to the learner. If they choose wrong a second time, it doesn’t have an overall impact, other than wasting their time. The solution to this, when appropriate, is to consider incenting precision. Let me give you some examples of what this means:
- In a multi-decision scenario about successfully interviewing, you tell the learner that if they answer more than 2 questions poorly, they won’t get the job.
- In a multi-decision scenario about teamwork, when the learner makes decisions about how to interact with others on the team, they see the team engagement meter go up or down based on their choice—and if the meter gets too low, they fail out of the scenario.
- In a multi-decision scenario about the application of safety policies, you could tell the learner that every decision has to be correct or else they’ll have to start over and repeat all 10 decisions in order to prove to the plant manager they know how to stay safe.
- Perhaps the learner gets two tries per scenario (even though there are four choices in a scenario) and if they can’t identify it correctly there is a consequence of some kind, like adding an additional scenario to their task list, repeating that scenario again at the end, or having to review that section of material. “Looks like you’re having a hard time with this one. Let’s go back to Section 3 where you can refresh yourself on the financial policy and then come back to try again.”
You get the idea. The options are endless. What you’re essentially doing is using behavior punishment or penalty to offset the learner’s temptation to guess. Those are harsh words but I mean them in the best possible way. You’re creating a situation in which it’s in their best interest to perform the best they can in order to avoid having to come back and do it all over again.
This approach isn’t always appropriate depending on the material, learner’s level of knowledge, and other factors so use your best judgement as to how and when to apply it. It often works best when applied in the context of a story and works even better if it mirrors a realistic consequence of too much failure (not getting a promotion and needing to apply again, needing to recertify for safety, having the restaurant shut down due to too many health violations, being removed from the project due to stakeholder dissatisfaction with performance, etc.).
This is the concluding article to the “4 Cs of Designing Meaning Scenarios.” If you haven’t already read Parts 1, 2, and 3 please do so – the meat of the message is contained in those articles. By crafting realistic Choices, letting the learner experience realistic Consequences, providing opportunities for them to make Connections about their choices, and allowing them to Correct their mistakes, you drastically enhance the meaning behind the learning experience and therefore, its effectiveness for the learner.
If you’re interested in having us help you create your next scenario, contact our Custom Solutions team.