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In this paper, we report on the formulation and early results of research supported by the National Science Foundation's Experimentation and Laboratory-Oriented Studies Division (DELOS). Using findings from cognitive science, we discuss the design of an intelligent tutoring system (ITS) that utilizes case-based reasoning (CBR) to scaffold undergraduate engineering students in their learning of introductory probability and statistics. Such a system will: Assist students in extracting the underlying common structure from engineering statistics • problems that illustrate the full range of engineering disciplines. Allow the students to generate, customize, and change a virtually infinite collection of • exercises that can be solved with the assistance of the ITS. The students can explore the effect of changes to solutions. Help students formulate and solve "practical" and "open-ended" problems, a skill stressed by • the ABET Engineering Criteria.

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