Development of a methodology for optimizing elicited knowledge

• Published in: Behaviour & information technology 1999-11, Vol.18 (6), p.413-430
• Main Authors: Chao, Chin-jung, Salvendy, Gavriel, Lightner, Nancy J.
• Format: Article
• Language: English
• Subjects: Exact sciences and technology; Human computer interaction; Information and communication sciences; Information retrieval systems. Information and document management system; Information science. Documentation; Miscellaneous; Personnel training; Sciences and techniques of general use
• ISSN: 0144-929X; 1362-3001
• DOI: 10.1080/014492999118841

In this paper a conceptual framework and an operational methodology is presented for describing the most appropriate knowledge elicitation method (protocol, interview, induction and repertory grid) for three classes of tasks (diagnosis, debugging and interpretation) and for experts with strengths in various factors of cognitive abilities. Using the dependent variables of: (1) total knowledge captured; (2) time to acquire knowledge; (3) knowledge quality; (4) efficiency of the knowledge elicitation method; and (5) importance of resulting data, experimental results indicate the various strengths of the four knowledge elicitation methods. The knowledge acquired is also significantly affected by the combined factors of expert's strengths in different cognitive factors and the method of knowledge elicitation used. Based on these findings, a Matching Index for combining tasks, knowledge elicitation methods and cognitive abilities of the expert is described. The outcome of this research provides theoretical and practical implications for Human Computer Interaction (HCI) and training of knowledge engineers.