Tailoring Retrieval to Support Case-Based Teaching

Robin Burke, Alex Kass

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 and 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.

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