Tailoring Retrieval to Support Case-Based Teaching

This paper describes how a computer program can support learning by retrieving and presenting relevant stories drawn from a video case base. Although this is an information retrieval problem, it is not a problem that fits comfortably within the classical IR model (Salton & McGill, 1983) because in the classical model the computer system is too passive. The standard model of IR assumes that the user will take the initiative to formulate retrieval requests, but a teaching system must be able to initiate retrieval and formulate retrieval requests automatically. We describe a system, called SPIEL, that performs this type of retrieval, and discuss theoretical challenges addressed in implementing such a system. These challenges include the development of a representation language for indexing the system’s video library, and the development of set of retrieval strategies and recognition knowledge that allow the system to locate educationally relevant stories.