Humans are still the best pattern-recognition machines on the planet! (At least for now.) Yes, we have suffered losses to man-made machine, in Jeopardy, chess, and recently the game Go. But we recognize complex patterns in everyday life and transform them into actionable steps, in ways that machines cannot. What’s our secret? Cognitive Flexibility. This trait allows us to diagnose, design, and problem-solve in highly unstructured situations where “rules” do not yet exist.
So, if we humans are so good at this cognitive flexibility thing, how can we use it to develop more effective skill acquisition programs?
Well, let’s think about the frustration that comes from creating a training scenario, and then finding that the trainees are not able to apply new knowledge skillfully, in real-world situations. What happened?
We can turn to cognitive science research for some clues. It’s not by accident that Dr. Rand Spiro named his learning methodology, “Cognitive Flexibility Theory.”
As Dr. Spiro explains it: “Cognitive Flexibility Theory is about preparing people to select, adapt, and combine knowledge and experience in new ways to deal with situations that are different than the ones they have encountered before.”
Perfect. This looks promising for skill acquisition!
Let’s return to the failed training scenario above. When we help a learner navigate through one situation optimally, they see the knowledge application from one perspective. Unfortunately, the real-world situation is often not close enough to that of the training, and the learner cannot recognize the opportunity to apply what they learned. Pattern recognition fails and their training goes unused.
Cognitive Flexibility Theory suggests three ways to help us improve this training scenario:
- Use Multiple Perspectives. Construct multiple situations where the learner applies the knowledge in different contexts. They will then be better equipped to A) recognize the training situation in real life, and B) respond appropriately to differences in context. With each perspective, the context changes while the conceptual approach to solve the problem (the mental model) remains the same.
- Use Case Studies. Immerse the learner in decision-making that emphasizes application of the knowledge, not the transmission of information. This allows the learner to practice the skill from different perspectives, creating virtual experience that can be translated to the real world.
- Don’t Over Simplify. Compartmentalization and linear simplifications can lead one to not recognize and apply patterns in less structured, real-life situations. Expose the big picture and how things are interconnected. Each time learners see another context through a different scenario, they better understand these interconnections.
So, there is hope for human kind as we compete with the machines for jobs. Our superior pattern recognition machinery, and innate cognitive flexibility are our secret weapons. It’s our collective mission to find ways to help people develop and hone these skills before it’s too late!
Spiro, Rand J., et al. "Cognitive Flexibility Theory: Hypermedia for Complex Learning, Adaptive Knowledge Application, and Experience Acceleration." Educational technology 43.5 (2003): 5-10.
About Syandus: Virtual immersive learning technology that transforms knowledge into real-world performance. We immerse participants in realistic virtual situations with one-on-one expert coaching that gives them experience making optimal decisions. Syandus Learning Modules combine cognitive science principles, the realism of game technology, and our customer’s proprietary content, to deliver rapid skill acquisition. Modules are cloud-based for easy deployment, fully trackable with embedded analytics, and can be used on any web-enabled device.