The ACT-R production-system theory (Anderson, 1993) has been extended to include a theory of visual attention and pattern recognition. Production rules can direct attention to primitive visual features in the visual array. When attention is focused on a region, features in that region can be synthesized into declarative chunks. Assuming a time to switch attention of about 200 msec, this model proves capable of simulating the results from a number of the basic studies of visual attention. We have extended this model to complex problem-solving like equation solving where we have shown that an important component of learning is acquiring more efficient strategies for scanning the problem.