Inductive reasoning is the ubiquitous mental activity of using existing knowledge to generate new knowledge that is likely, though not guaranteed, to be true. Inductive reasoning is required whenever people need to fill in gaps in their knowledge with “best guesses” about the state of the world. Generalizing that all snakes are black after encountering three black snakes, predicting rain in the afternoon upon seeing dark clouds in the morning, and using the analogy that an atom is like the solar system to infer new properties of atoms are all examples of inductive reasoning.
In the mid-1900s, psychologist Jean Piaget developed a highly influential developmental model of human thought that posited that inductive reasoning capabilities—and other kinds of reasoning capabilities as well—develop slowly from infancy until about 11 years old. Infants and toddlers were believed to be unable to reason but rather to be bound to their perceptions of their immediate environment. Children aged 7 to 11 years were thought to be able to do some simple reasoning but only with very concrete problems. Finally, after about the age of 11, children were thought to have fully developed abstract reasoning systems that could be used in any situation.
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Today, in contrast, it is widely believed that inductive reasoning shows remarkable continuity across the life span. It is subject to similar strategies, influences, and biases in both children and adults. Limitations that were previously identified as resulting from an underdeveloped reasoning system are now more often attributed to a lack of content knowledge among children. For example, it would be difficult for a child—or an adult for that matter—to learn to diagnose diseases without first having a more general understanding of how symptoms and diseases are related. In other words, content learning and use of reasoning skills are now believed to go hand in hand.
Perhaps not surprisingly, people are most inclined to draw inferences between things that are highly similar to one another. For example, when reasoning about animal categories, people are more inclined to infer that “cheetahs have spleens” after finding out that “tigers have spleens” than after finding out that “mice have spleens.” People also prefer to use typical things, rather than atypical ones, as the basis for their inferences. For instance, it is more compelling to transfer knowledge from robins to canaries than from ostriches to canaries because a robin is a more typical example of a bird. Influences of similarity and typicality are seen both in adults and in children as young as 2 years old.
People are also influenced by the perceived transferability of the property under consideration. For example, people are willing to transfer the eating of alfalfa from one rabbit to another, but they are not willing to transfer a scratched surface from one television to another. Interestingly, the property under consideration can also influence the perceived similarity of two situations. Adults, for example, perceive whales and fish to be highly similar when reasoning about whale behaviors, but perceive whales and bears as more similar when reasoning about whale biological properties. Such property influences have been seen both in adults and in children as young as 4 years old.
Inductive reasoning is very often contrasted with another kind of reasoning known as deductive reasoning. Deductive reasoning refers to the use of formal rules of logic to produce new knowledge that is guaranteed to be true to the extent that the available knowledge on which it is based is also true. For example, using the knowledge that “All living animals breathe” and “Fido is a living animal” to determine that “Fido breathes” is an example of deductive reasoning. Deductive reasoning can be applied only in situations that conform to certain logical structures. Inductive reasoning differs in that because it is not based on formal rules, it cannot guarantee a true conclusion, but it can offer highly likely conclusions in a much wider range of situations.
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