Symbolic and associative theories ha\e l)ccn claimed to be able to account for concept learning from examples. Given that there seems to be enough empirical evidence supiwrting both claims, we have tried to integrate associative and symbolic Tomiulations into a single com|Mitational model that abstracts infonmation Trom empirical data at the same time that it takes into account the strength with which each hypothesis is associated with lewanL The model is tested in a simulation of pigeon data in a fuzz\ concept learning task, where only a few abstractions are stored in representation of ail the training patterns and strengthcd or weakened depending on their predictive value.

This paper describes an approach to cognitive engineering which promotes a symbiosis between the theories and methodologies of cognitive psychology and the practices of human-computer interaction design. We ground the description of our approach in a particular design problem: the development of computerised decision support in medical intensive care. We review the psychological literature of medical reasoning and decision making, highlighting its potential to inform the design of medical computerised aids. We also discuss how addressing this design problem may in turn benefit cognitive theory. This is followed by a brief description of our proposed methodology.