Empirical evaluation of decision tables for constructing and comprehending expert system rules

Abstract

Two studies were designed to evaluate the efficiency of decision table representations for constructing and comprehending expert system rules by nonprogrammers with no experience in either knowledge engineering or expert systems. The first study compared the speed and accuracy of a decision table editor for constructing rules in a tabular representation relative to a standard text editor. Rules were constructed faster and more accurately with the decision table editor than with the text editor. The second study focused on the representational value of decision tables for comprehending expert system rules. In a verification task, subjects responded to questions of different types as accurately and rapidly as possible on the basis of the logical structure of a set of rules represented in either a decision table or textual format. The decision table showed an advantage only in situations where the diagrammatic, integral representation of the decision table expedited the perceptual and symbolic matching processes involved in the search.