Complete “Sentence Verification” on the ZAPs site. Because typical and non-typical instances of a category are stored at the same level in Collins and Quillian’s model, how can they explain the typicality effect?
In the Collins and Quillian’s model of semantic memory, typical and non-typical instances of a category are indeed stored at the same level. The model proposes that semantic information is organized in a hierarchical manner, where each category is represented by a node, and the relationships between categories are represented by connections or links between these nodes. Activation spreads through these connections, allowing for the retrieval and processing of information in a hierarchical manner.
According to the model, the typicality effect can be explained through the concept of spreading activation. When a person is presented with a stimulus that belongs to a specific category, such as “dog” for instance, the activation spreads from the node representing the concept of “dog” to other related nodes in the semantic network. These related nodes can be other instances of the category “dog,” as well as properties or attributes associated with dogs, such as “barks” or “has fur.”
The strength of the activation decreases as it moves further away from the original stimulus, leading to a decrease in the ease of access to that information. In other words, the more typical an instance is of a category, the stronger the connection between that instance and its category node, and therefore the easier it is to access information related to that instance.
For example, when presented with the stimulus “bird” in a semantic memory task, the node representing the category “bird” would receive a high level of activation. This activation would then spread to other related nodes, such as “robin,” “sparrow,” or “penguin.” Since robin and sparrow are more typical examples of birds compared to penguins, the connections between the nodes representing robin and sparrow and the bird category node would be stronger. As a result, accessing information about robin or sparrow would be faster and more efficient compared to accessing information about penguins.
The typicality effect can be observed in various cognitive tasks and experiments. For instance, in a sentence verification task, participants are presented with sentences and are asked to determine whether they are true or false based on their semantic knowledge. When the sentence refers to a typical instance of a category, such as “a robin is a bird,” participants would respond more quickly compared to sentences referring to non-typical instances, such as “a penguin is a bird.”
This difference in response times can be attributed to the efficiency of accessing information due to the strength of connection between typical instances and their category nodes. The stronger the connection, the faster the activation spreads, leading to quicker access to relevant information and faster response times.
Collins and Quillian’s model has provided a valuable framework for understanding the organization and retrieval of semantic information in human memory. However, it is important to note that this model has been subject to criticism and has been refined and expanded upon by subsequent theories and models of semantic memory. It is worth exploring these alternative theories and considering their perspectives on the typicality effect.
Overall, the typicality effect in Collins and Quillian’s model can be explained by the spreading activation process, where stronger connections between typical instances and their category nodes result in faster and more efficient access to information. This model has contributed to our understanding of semantic memory and its implications for various cognitive tasks.