Pioneering work by De Groot and Miller in the 1940s and 50s suggested that the concept of chunking may underlie many processes of perception, learning and cognition within humans and animals. In this article we summarise the major sources of evidence for the presence of chunking mechanisms, and consider how such mechanisms have been implemented in computational models of the learning process. We distinguish two forms of chunking: the first deliberate, under strategic control, and goal-oriented; the second automatic, continuous, and linked to perceptual processes. Recent work with the EPAM/CHREST family of computational models has produced a diverse range of applications of perceptual chunking within areas such as verbal learning, expert memory, the use of multiple representations, and language acquisition. This article focuses on these recent successes, and uses them to illustrate the implementation and use of chunking mechanisms within contemporary models of human learning.