acquisition literature called contextual interference (Shea & Morgan, 1979). Contextual interference refers to a learning benefit observed when the items to be learned are randomly intermixed across training blocks rather than repeated in blocks (for a review, see Magill and Hall, 1990). That is, when identical items are blocked together during training, post-training performance is worse than when different items are intermixed. Although primarily studied with motor skill learning task, contextual interference was originally reported in a verbal paired associates task (Battig, 1966, 1972) and has been observed in other non-motor tasks (e.g., Carlson et al., 1989). The benefits of mixed-item blocks are apparent only some period of time after practice, indicating that the effects are primarily long-term. The source of contextual interference is not well understood. At present, it is primarily an empirical phenomenon. Most accounts assume that it emerges because blocked practice is not sufficiently demanding to produce optimal effort or attention. Consistent with this view, contextual interference is reduced or eliminated with more complex tasks (see Wulf & Shea, 2002). Across the various accounts of this complexity effect, the dominant theme is that as complexity increases, learners benefit more from the opportunity to repeat and refine their responses on successive trials. There is also debate regarding whether children show the effects of contextual interference as adult learners. Some studies suggest children show normal contextual interference (e.g., Edwards et al., 1986) whereas others show no effect in children (e.g., Del Rey et al., 1983). Moreover, as with adults, more difficult or complex tasks show less contextual interference (Magill & Hall, 1990). Thus, the absence of contextual interference in some studies with children may simply be another manifestation of the task complexity effect. Similar to Contextual interference bears an intriguing similarity to a phenomenon observed during the training of neural networks called catastrophic interference (McCloskey & Cohen, 1989). Catastrophic interference occurs when a network is trained to criteria on one set of mappings, and then switched to a new set, at which point it loses access to the initial mappings. In a sense, rather than forming a set of connections that would preserve the knowledge it acquired in the first task, the network optimizes its performance completely to the new task. The solution to this problem is simply to interleave the training sets so that the network is forced to optimize its behavior in a way that is sensitive