The goal of the seminar was to search for new commonalties in the fields of expert systems and intelligent tutoring systems. Since the academic research, the industrial developments and the practical applications have greatly matured the fields of expert systems and intelligent tutoring systems during the last decade, valuable insights could be achieved by pursuing such a comprehensive goal.

Originally, the two fields had relatively separate, although in many respects similar, goals and agendas. The task of developing expert systems was seen as encoding the lmowledge and the competence of human experts. In a similar fashion, intelligent tutoring systems were intended to capture expert knowledge plus the added pedagogical expertise of the sldlled teacher. However, the agenda of tutoring systems research first moved toward the special problems of modeling the not-yet-enlightened student and how human knowledge can be conveyed, while the work on expert systems focused on particular problems at the limits of human capability.

The presentations and discussions of the seminar focused on the knowledge that is shared between a teacher and a student, among practitioners of some field of expertise, and among various participants in complex and dynamic work and training situations in general. The seminar revealed that both expert- and instruction systems are improved by explicit representations of the objects and actors in work situations. In such situations, explanations play an important role, both in lraining and co-ordinated man-machine work.

While expert systems are mostly focused on the representations of the situations they are intended to address, tutoring systems are frequently tailored to the training for specific situations. As systems become applied to increasingly complex work and training situations, these differences are becoming less important. As both fields have matured, the shared focus has thus become more important and more achievable. With training emerging as an ever-higher cost for business and industry, its automation has become increasingly valued, as has the possibility of extending human capability with machine expertise. With a more unified understanding, these systems can thus be made more useful.

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