Knowledge acquisition is not only the most important but also most difficult task knowledge engineers face when they begin to develop expert systems. One of the first problems they encounter is the need to identify at least one individual with appropriate expertise who is able and willing to participate in the development project. They must also be able to use a variety of techniques to elicit the knowledge that they require. These include such traditional knowledge acquisition methods as interviewing, thinking-aloud protocol analysis, on-site observation, and repertory grid analysis. As expert system applications have become more complex, knowledge engineers have found that they must work with and tap the domain knowledge of not one but several individuals. They have also discovered that the traditional methods do not work well in eliciting the knowledge residing in a group of individuals. The complexity of the systems, the difficulties inherent in working with multiple experts, and the lack of appropriate tools have combined to make the knowledge acquisition task even more arduous and time consuming.
Group Decision Support Systems (GDSS) have been proven to be useful tools for improving the efficiency and effectiveness of a multiplicity of group activities. It would appear that by bringing experts together in a GDSS environment and using computer-based tools to facilitate group interaction and information exchange, a knowledge engineer could eliminate many of these problems. This research was designed to explore the possibility of using a GDSS environment to facilitate knowledge acquisition from multiple experts. The primary research question was "Does A GDSS environment facilitate the acquisition of knowledge from multiple experts__ __"
The principle contributions of this research are (1) demonstration of the first use of a GDSS environment to elicit knowledge from multiple experts; (2) establishment of a methodology for knowledge acquisition in a GDSS environment; (3) development of process models for acquiring knowledge; (4) development of guidelines for designing and evaluating group support tools; and (5) recognition of some implications of using a computer-supported cooperative approach to extract knowledge from a group of experts. (Abstract shortened with permission of author.)