Concept knowledge, or concept learning, also known as concept attainment and category learning is a method of categorizing different objects, or exemplars, to list their attributes and distinguish one from another. Within this approach, concepts are seen as mental categories according to which ideas, objects or events with common features are classified, compared and contrasted. There are different theories of concept learning, but most of them are based on learning from examples and induction and avoid abstraction.
Prototype and exemplar theories are two contrasting views on category learning. According to prototype theory, we percept new objects, ideas and events basing on examples we have already experienced before. It means that beneficial are previous experiences; they make up a selective advantage. Among those examples there are those which are used more frequently; they form a central tendency. Other examples are on the periphery of the category. Thus, semantic similarity is used to abstract from central examples and such idealized tendencies representing the category are called prototypes. Prototypes are defined as “a generic or idealized representation of a conceptual category” (Harley 2008). Prototype theory includes a notion of typicality effects introduced within evolutionary approach. This effect involves successive work of memory, logical reasoning, judgment, language and finally categorization.
Typicality effects are demonstrated during picture naming tasks, as a robin, for example, is more typically accepted as a bird, and penguin is not as typical as a robin or a canary are, because we prepare to see some small creature with a beak, with wings and able to fly and sins. We make inferences through visual processing and object recognition, singling it out of others and thinking of relations between concepts. Many tests have revealed mediated priming in picture identification. Harley underlines that “the relation between the picture and the meaning gradually became looser” (Harley 2008). Further, the concepts and inferences are provided with definitions and thus can become deductively valid.
However, the problem is that not all the categories are so prototypical and representative to be easily classified.
Exemplar theory is alternative to “prototypicality”. If the latter means that some typical concept provides representation for further perception, exemplar theory makes a stress on individual experience we remember of almost all the examples (or instances) of the category. We use our memories to classify a new idea comparing it with what is similar. And the extent to which the new entity is close to those resembled members of the category. It is significant to underline that examples are stored in memory verbatim, and thus these are individual properties that matter. They are not abstract and they do not provide a system of demands to a new member (Reisberg 2006). According to this theory, picture identification differs from that one in property theory. It gives a space for more assumption, but still there are difficulties remarked when entities have many features not saved in memory. The disadvantage of the theory is that it is not known how group membership is defined. Later it has been found out that this way of concept learning is more typical for young people, on early stages of getting knowledge. Later properties and generalizations are formed.
All in all, each theory provides new understanding of how we learn, know, remember and talk, and at the same time each has its weakness. Therefore, rational are those models where exemplar and prototype based theories are combined and compromised.