State Models of Paired Associate Learning: The General Acquisition, Decrement, and Training Hypotheses
Donald L. Fisher University of Massachusetts
Older adults learn more slowly than younger adults on almost all tasks. Perhaps this is most evident when one considers the learning required to master the ever changing new technologies. Older adults frequently struggle to learn these new technologies. Even the most simple interaction sometimes proves frightening. For example, older adults by and large still choose to ignore interactions with automated teller machines (ATMs) whenever possible. Anything that can be done to reduce the time that it takes older adults to learn how to use the new technologies is not only a gain in efficiency; it may well be the difference between older adults' taking advantage of and not taking advantage of all that the new technologies have to offer. In many cases, the learning required of older adults in order successfully to interact with the new technologies is identical to the learning required in order to master more pedestrian paired associate tasks ( Kausler, 1992). Thus, if one could reduce the time that it took older adults to master these latter paired associate tasks, in principle, one could reduce the time that it took older adults to master the former more practical tasks.
Three general conclusions follow from the work reported in this chapter. First, and primarily of theoretical importance, I find that one and the same formal model characterizes the performance of younger and older adults on paired associate tasks. Of course, the values of the parameters in the model are influenced by the age of the subject (older adults do learn more slowly than younger adults), not only the structure of the model. Second, and of more substantive importance, I find that a detailed analysis of the effect of aging on the component