Both human learners and Case-Based Reasoning systems have applied metacognitive strategies such as self-questioning to improve the learning process. Whereas case-based reasoning systems do not allocate attention to reasoning strategies in order to facilitate strategy selection, previous work on attention in human thinking has focused on the selection of domain objects. We describe a computational model of metacognitive attention which integrates metacognitve approaches in case based reasoning with the concept of attention which is applied to the reasoning process itself. An example of our implementation, lULJAN, will illustrate the process of allocating metacognitive attention