Encouraging unitary and compositional representations for relational concept learning.

Current theories of relational learning based on structure mapping emphasize the importance of compositional representations, based on the concept's interconnections among its elements. We consider the possibility that relational concepts can also be represented unitarily, whereby the concept is a property of the stimulus as a whole. The distinction between compositional and unitary representations of relational concepts is a natural consequence of structure-mapping theory, but its psychological implications have not been explored. We report three experiments in which we examine how encouraging subjects to represent relational concepts compositionally versus unitarily affects learning on classification- and inference-based category learning tasks. Our findings showed that encouraging unitary representations led to better learning than encouraging compositional representations, especially for inference-based learning. We conclude that unitary representations incur less cognitive load than structural alignment of compositional representations, and thus may be the default for everyday relational learning and reasoning.