What are good ways of using natural language dialog in intelligent tutoring systems? A role with high potential payoff is to support the meta-cognitive process of selfexplanation. In previous experiments involving the PACT Geometry Tutor, we found that students learn with greater understanding, when they are required to explain their solutions steps "by reference", that is, by naming the rule that was used. However, the tutor may be even more effective if students explain their solution steps in their own words and if the tutor helps them, through dialog, to improve their explanations. An exploratory experiment with a tutor version that did not do any natural language processing, strongly suggested the need for natural language dialog. Without feedback from the tutor, students provided few free-form explanations in response to the tutor’s prompts. Of the explanations that they did provide, only a small portion were correct and complete. During the experiment, we also identified a number of dialog strategies that we plan to implement in the tutor.