Proceedings of the Annual Meeting of the Cognitive Science Society

Different situations may require the presentation of different types of examples. For instance, some sit- uations require the presentation of positive examples only, while others require both positive and nega- tive examples. Furthermore, different examples often have specific presentation requirements: they need to appear in an appropriate sequence, be introduced properly and often require associated prompts. It is important to be able to identify what is needed in which case, and what needs to be done in pre- senting the example. A categorization of examples, along with their associated presentation requirements would help tremendously. This issue is particularly salient in the design of a computational framework for the generation of tutorial descriptions which include examples. Previous work on characterizing exam- ples has approached the issue from the direction of when different types of examples should be provided, rather than what characterizes the different types. In this paper, w e extend previous work on example char- acterization in two ways: (i) we show that the scope of the characterization must be extended to include not just the example, but also the surrounding con- text, and (ii) w e characterize examples in terms of three orthogonal dimensions: the information con- lent, the intended audience, and the knowledge type. We present descriptions from text-books on USP to illustrate our points, and describe h o w such catego- rizations can be effectively used by a computational system to generate descriptions that incorporate ex- amples.