The proposed research will examine the role of attention in acquiring automatic skills and transferring them within and between tasks. The main theoretical focus will be on developing a theory that explains how acts of attention during training encode traces into memory to build up a task-relevant knowledge base, and how acts of attention at transfer retrieve traces from memory to support automatic performance. The theory will build on existing theories of attention and automaticity, extending and generalizing them. The main empirical focus will be on visual search, which is a dominant paradigm in research on attention and automaticity that has important practical implications (e.g., for driving, navigation, and supervisory control). Experiments will address how automatic skills acquired during training on visual search transfer to and from other tasks (counting and categorization) performed on displays similar to and different from the ones experienced during training. The proposed research is significant theoretically and practically. The ability to perform automatically is a major factor underlying skilled performance and it is important to understand it better. The proposed research will increase our understanding by distinguishing between competing theories of automatization and integrating previously unrelated theories of automatization, attention, and categorization. The experimental and theoretical results on transfer will have important implications for education and industrial training, providing a principled way to determine whether experience gained in one setting (e.g., the classroom) will generalize to another (e.g., the workplace) and a principled way to design training programs and select training examples to maximize generalization and optimize skilled performance.
