Textvision: Elicitation and Acquisition of Conceptual Knowledge by Graphic Representation and Multiwindowing

Abstract

Knowledge engineering can be considered as an influential paradigm for the design of complex information systems. Moreover, it will ultimately be of importance in all those situations where humans are to be taught and are supposed to be learning by means of computers at their own pace and using their own style of learning. Expert systems which are designed to help in human tasks such as diagnostics and to interpret patterns of data, are expected to tackle complex material and may even change the frontiers of cognitive psychology. Because knowledge-based systems can assist the mental operations of humans, it will be important to preserve the opacity and comprehensibility of their knowledge bases and the mechanisms they use to infer new facts from it. In the last decade several computer-based instructional systems were predicated as being “intelligent”: Bip, programming in basic (1976); Excheck, logic and set theory (1981); Spade, programming in Logo (1982); LMS, algebraic procedures (1982); Quadratic, quadratic equations (1982); Guidon, diagnostics of infectious diseases (1982); Algebra, applied algebra (1983). Since the main purpose of these systems was prototype development, they rely mainly on rule-based knowledge, particularly in the algorithmic components. Once there is a variety of software tools for the development of expert systems in several areas we will we able to elaborate on the more fuzzy and associative types of knowledge (Hofstaedter, 1985).