This paper details the theoretical foundations of a system for teaching repertory grid concepts and the practical approach for its implementation. This will involve a discussion of the development of the production program for KAGES (Knowledge Acquisition for Geographic Expert Systems) and the enhancements necessary to make it an effective teaching tool. Initial student reaction to the method will also be presented.
The traditional approach to knowledge acquisition for expert systems has been via interview. However deeper knowledge can be elicited using repertory grid techniques which get domain experts to rank objects against concepts. The technique based on Kelly's Personal Construct Theory has been well proven by Boose et. al. The current study grew out of the development of a repertory grid program, developed for the KAGES toolkit, which will consist of several knowledge acquisition tools for use in the development of spatial expert systems. By expanding the system to show intermediate workings and grids it was found that the system was a good method of explaining repertory grid techniques and the associated hierarchical clustering which is very difficult to demonstrate using traditional techniques.
The system initially interacts with the student over a chosen domain (which does not have to be geographic) to elicit a series of objects or classifications to create a grid. The domain can be either of the students' or the facilitators' choice. The student is then stepped through the various manipulations of the grid. These grids are then subject to hierarchical cluster analysis which the student is also stepped through until a hierarchy chart showing clustering is produced.
