A Broader Definition of Learning Can Help Stimulate Interdisciplinary Research

We often imagine learning through the lens of cramming for tests or teaching dogs to sit, but humans and other mammals aren’t the only entities capable of adapting to their environments—schools of fish, robots, and even our genes can learn. new behavior, explain Jan De Houwer and Sean Hughes (Ghent University) in new Psychology Science Perspective article. Embracing a broader definition of learning that includes any behavioral adaptations developed in response to the regular features of an environment can help researchers collaborate in the fields of psychology, computer science, sociology, and genetics, De Houwer explained in an interview.

“Most people think of learning as some kind of mechanism for storing new information, but this makes it very difficult to compare learning in different systems because different systems may use different mechanisms for storing information,” says De Houwer. “We define learning as a change in the way a system responds to its environment—that is, as learned behavior.”

Like Darwin’s theory of evolution, De Houwer and Hughes’ functional definition of learning focuses on how a system adapts to its environment, regardless of the mechanisms by which such adaptation can occur. The “system” in question can be an individual organism, a part of an organism such as genes or the spinal cord, or a community of organisms. In fact, adds De Houwer, evolution itself can be understood as a form of learning in which an animal species is seen as a system that adapts to its environment.

“Because our definition of learning is ‘mechanism free,’ it allows interaction between scientists studying learning in different systems,” says De Houwer. “It breaks down barriers between different sciences and enables an exchange of ideas that are bound to promote the study of learning in general.”

As well as supporting comparisons between learning in different types of systems, this definition can also help researchers to take a closer look at how these systems can influence one another’s learning, write De Houwer and Hughes. Corn plants may learn to become more drought tolerant, for example, because their genes have an epigenetic response to dehydration that prompts their cells to retain more water, ultimately influencing the learned behavior of the entire plant.

Learning can also occur at the group level, such as in a school of fish, due to the learning of some but not all members in the group, adds De Houwer. A fish in the principal may learn to avoid being shipwrecked after repeatedly encountering sharks there, for example, while a fish in the back of the school may engage in similar behavior simply by continuing to follow the fish in front of them without learning about the shipwreck.

This analysis can also be applied to the study of robots and artificial intelligence. While each can be studied separately, a robot’s ability to learn how to navigate obstacles also depends on how its algorithm responds to the environment, the researchers explained.

However, it is important to note that a system cannot be described as learning just because its behavior has changed in response to the environment. A system can only be said to have learned something if it changes the way it responds to a stimulus as a result of regularities in its environment, such as repeated exposure to a stimulus or the simultaneous occurrence of stimuli, says De Houwer. Learning researchers examine the conditions under which regularity in the environment changes behavior, he continues.

Developing an appropriate definition of learning can help scientists communicate existing findings and promote new interdisciplinary research, De Houwer and Hughes concluded.

“Definitions are tools at the service of better science,” they wrote. “Our definition allows scientists to share knowledge and thereby explore new ways of studying learning in different systems.”

– This press release was originally published on the Association for Psychological Science website