Sherlock is an intelligent tutoring system designed to teach people to build simplified knowledge representations (graphic maps) to facilitate learning of a text. Previous attempts to automate instruction in graphic mapping have had problems because they attempted to diagnose a learner's misunderstandings by looking at a finished graphic map. Sherlock uses a knowledge-based approach to diagnose a leamer's misunderstandings by looking at the knowledge and processes that lead to a learner's graphic map, rather than the completed map. In Sherlock's model a semantic network is used to represent the knowledge in the text. A production system models the strategy for constructing a gniphic map by initiating spreading activation on the semantic network, and interpreting the resulting activation patterns. In a limited evaluation Sherlock was able to correcdy determine if a construction was appropriate 9 6 % of the time.

Computer-based simulations are a valuable teaching tool because they permit a learner to explore a phenomenon on his o w n and to learn from his mistakes. T w o factors, however, limit the use of computer simulations in teaching: good simulations are hard to build and learners can flounder with just a simulation. W e have built HeRMiT^, a case-based tutor that integrates a simulation with a library of videotaped stories. The stories make up for any lack of depth or fidelity in the simulation by facilitating the generalization and application of underlying principles.