A greedy knowledge acquisition method for the rapid prototyping of knowledge structures
Claus Möbus, Heiko Seebold, Hilke Garbe · 2005
The main goal of this paper is the presentation of a new GReedy knowledge Acquisition Procedure (GRAP) for rapid prototyping of knowledge structures (KS) or spaces. The classical knowledge acquisition method for this [2] is even for domain experts cognitive demanding and computational complex. GRAP interactively generates an online knowledge acquisition schedule so that experts only have to provide simple nonredundant judgements about the (learning / cognitive) precedence in pairs of (learning / cognitive) objects. From these data GRAP generates a Hasse diagram of the surmise relation from which the knowledge structures and optimal user-adaptive learning paths can be derived. In a case-study we developed with three expert software engineers a knowledge structure and optimal learning paths for 23 software design patterns within a few hours.