Appropriate Responses to the Challenge of Situated Cognition for Knowledge Acquisition

The dominant knowledge modeling paradigm in the KA eld assumes that old knowledge expressed symbolically (i.e. problem-solving strategies or ontologies) is a productivity tool for building new knowledge bases. That is, it assumes that knowledge is context-independent. Researchers of situated cognition (SC) claims that knowledge is mostly context-dependent and that concepts elicited prior to direct experience are less important than functional units developed via direct experience with the current problem. We argue that there is suucient evidence to support some of the SC view; i.e. we may need to modify the knowledge modeling approach. Symbolic approaches exist which could be said to handle SC; e.g. abduction, veri-cation & validation tools, repitory grids, certain frameworks for decision support systems, expert critiquing systems, ripple-down-rules, and ripple-down-models. However, such approaches need careful assessment in order to test their appropriateness as a response to the challenge of SC. Hence we propose a metrics program to assess the impact of SC and the success of our symbolic KA tools for handling SC. Interestingly, some of the symbolic tools we review for handling SC also assist us in the metrics program.