Teacher resources and professional development across the curriculum

Teacher professional development and classroom resources across the curriculum

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Title of course:  Neuroscience and the Classroom: Making Connections

Neuroscience and the Classroom: Making Connections

Unit 5: Building New Neural Networks


Section 7:
Regression: not failure but a critical component of building and rebuilding skills

Previous: Section 6 Next: Section 8

Q: What is failure?

People hate failure. In school, failure is a major source of fear and frustration for students and teachers alike. Our attitude toward failure may well be the result of the ladder metaphor's implication that good learning and, therefore, good teaching, are marked by steady forward progress toward mastery. "They learned this last week, and today it was as though they had never seen it before." Yet, regression, or performance that is typically misinterpreted as failure, is both inevitable and necessary for learning.

Once we understand the connection between performance and context, the inevitability of regression becomes obvious, especially in school, where teachers work to create conditions that support scaffolded and optimal performance. If conditions change, for example when the support of the teacher is no longer available or motivation wanes, performance falls back to the functional level. Moreover, conditions constantly change. Sometimes, they change within us, when we don't get sufficient sleep or become upset or bored. Even our most basic skills, like our ability to walk, can regress under the pressure of traumatic conditions. Some parents, for example, at the funeral of their young child have fallen to the ground and crawled because they quite literally lost the ability to walk for that moment, reminding us that in extreme conditions even seemingly simple automatic skills degrade into their underlying basic skills.

Sometimes, conditions change because the domain in which we are asked to (top)

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perform changes: driving a backhoe is not the same as driving a car. Although a skilled adult driver may more quickly learn to operate a backhoe, at first he may look like a child—exploring the various levers, lurching forward, and stalling the engine. Furthermore, writing a science lab report is not the same as writing a history paper or writing an analysis of a poem. The forms are different, the concepts are different, and the kinds of thinking are different. So, while Jenny may be a terrific writer in the biology lab, she may be completely lost when asked to write a history paper or when trying to compose a letter explaining personal feelings to her father.

Even when teachers sustain or successfully re-create highly supportive conditions within the same domain, their students' performance will fluctuate, showing signs of improvement and regression—two steps forward, one step back. That's the rhythm of learning, the rhythm of constructing new neural networks. It's a process of building and rebuilding that allows us to continue to improve, each time advancing a bit further from a more solid base. Integrating skills into increasingly complex systems of representations and then abstractions is difficult work, involving considerable trial, success, and error. Each success brings us closer to the limit of our ability or understanding until we stumble, go back a bit, and start again—learning from both our progress and regression and slowly building stable neural networks.

Previous: Section 6 Next: Section 8



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