QUE is an exploratory environment for users of rule based intelligent systems. Its original motivation was the question of how to analyze and explain the discrepancies in rule-based intelligent tutoring systems, between “near miss” incorrect responses of a student and the system’s knowledge of the “correct” line of reasoning. It is currently under development as a suite of techniques which provide explanation by supporting the exploration of a system’s reasoning processes. This paper describes some of the exploratory modes, the underlying mechanisms that support them, and a number of ways in which these modes and mechanisms might be incorporated into intelligent tutoring architectures.