We Think – Therefore We Learn. Why Psychology is Still Relevant in the Age of Neuroscience

Nearly everything we thought we knew about the human brain changed when we started putting live subjects into functional Magnetic Resonance Imaging machines (MRIs) about 15 years ago. You might think that with the invention of the fMRI and other brain imaging technologies psychology has gone the way of phrenology and other pseudo-science, but this is not the case.

Cognitive science is a branch of psychology that attempts to explain human behavior by understanding how we think. Like cosmology, quantum physics, and many other branches of science, cognitive psychology employs models to describe something that can’t be directly observed.

While it may not be as “sexy” as neuroscience right now, many cognitive psychology models have stood the test of time, allowing us to consistently predict human behavior. In fact, many elements of these models have been validated and expanded by new discoveries in neuroscience. As a learning professional, you are probably at least a bit aware of some of the models.

Here are a few of the ones I find most useful. (Brings me back to my Master’s in Education program at Capella University — how about you?.)

Behaviorism attempts to explain how we learn as a reaction to an outside stimulus that becomes learned through repetition. While many today think that this model is too limited to describe the full range of human behavior, there are some types of learning experiences for which it works quite well. It also serves as one of the foundations of machine learning and neural networks. You may know it better by a more fashionable, recent name – “reward learning.”

Constructivism assumes that every person is motivated to learn by an inner desire to make sense of the world. In this model, every learner is self-directed and a teacher or trainer plays the role of facilitator, helping the learner discover and “construct” his or her own meaning. This model is the foundation for learner-centered approaches to training and education.

Piaget’s Stage Theory of Cognitive Development recognizes that a child’s ability to process information evolves as the child grows and the brain and body develop. While his work targeted children, many learning professionals have applied his theory to adult learning. If you’ve ever employed the concept of scaffolding or schemas to support learning, you’ve leveraged his work. He was also one of the first people to recognize that intelligence is not a fixed trait.

Gagne’s Nine Events of Learning – Robert Gagne recognized what he called conditions or events which must be present in order for learning to take place. While he developed his theory based solely on his own observations, it tracks very well with what we know about how the brain processes, encodes and retrieves information. It tracks so well, in fact, that I leverage his work in my Essentials of Brain-Based Learning workshop for the Association of Talent Development (ATD).

The Ebbinghaus Learning Curve, Forgetting Curve, and the Spacing Effect

Long before neuroscience even existed, Hermann Ebbinghaus applied the scientific method to study how we learn, remember and forget, by using himself as his subject. He first published the results of his experiments in 1885, yet his diligent attention to detail has kept his work relevant today. An older contemporary of Albert Einstein, Ebbinghaus was a true polymath, performing at genius level in multiple scientific disciplines. If the L&D field has our own “Einstein,” Ebbinghaus is that guy.

Psychology continues to leverage neuroscience

Today, psychology and neuroscience are collaborating to advance our understanding of the most complex object in the known universe – the human brain. While a few are still debating the value of neuroscience to Learning and Development, the American Psychological Association (APA) has recognized the applications of neuroscience to understanding human behavior since at least 2011.

Other sciences that come into play

In addition to psychology and neuroscience, the learning professional can gain insights from chemistry, mathematics and probability, physics, anthropology and many other branches of science. Discarding what works and is still validated by the scientific method would be a bit like refusing to employ geometry once Newton and Leibniz invented calculus.

That just does not compute.

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