Strong and durable learning can happen without incentives and reinforcements. How do we make the most of that insight? Part One on latent learning.
Before Edward Tolman's maze experiments (see this post, and this post, for the full story) and subsequent theories about "cognitive maps," it was conventional wisdom that learning only occurred with incentives and reinforcements. All learning, it was assumed, was behavior modification in response to stimuli. (The Pavlovian response is the most famous reference for this approach). Tolman's experiments and the "latent learning" theory that followed provided a new conceptual frame. That is, learning can also happen cognitively, in the absence of stimulus, and without obvious incentive or reinforcement.
Tolman's claims that there is a cognitive dimension to learning set off more experimentation as cognitive psychologists attempted to replicate the results, and behaviorists attempted to prove them wrong (see this article for a helpful summary on the debate). At stake in this argument was a basic conceptual disagreement about human nature.
We don't need to dig that deep; no experiments have thus far disproved Tolman's theory. Perhaps, some scientists have concluded, the "map" metaphor is insufficient, or distracting, since it overly abstracts some physiological alterations that occur during learning. But I think the image of cognitive mapping is quite useful, given the shift in usage of the term. In contemporary language, “mapping” evokes much more than a strict cartographic function. It has also moved beyond the two dimensional world of paper maps, to encompass computer applications that help us track our thoughts and brainstorming, especially for strategic planning. In other words, mapping itself has become a useful metaphor for describing the contours and larger context of more specific ideas, concepts, and tasks.
As we think about the difference between performance support and performance learning, cognitive mapping remains a useful way to help us strategize about how best to design learning projects in the workplace. When, for instance, might it be better for learners to spend a little more time learning the larger context of a task, free of more distracting structured incentives, so that their performance will improve in the long term? We'll consider that question in part two of this topic.
Morris Davis, PhD, is an Associate Professor at Drew University and Senior Learning, Performance, & Design Consultant to Ontuitive. Twitter: @morleydj.