Expertise and age effects on knowledge activation in chess

Novice, intermediate, and expert chess players of various ages, playing with two chess pieces on a quarter-section of a chessboard, performed a simple task to detect that the king is in check or is threatened with being in check. Age slowed response for both tasks. An interaction of task and skill revealed differences in diminishing response time between check and threat tasks as skill increased; experts were equally fast on both tasks. Measures of speed and working memory were negatively related to age but unrelated to skill. Skill did not mitigate age-related effects on speed of detection. These results suggest that knowledge-activation processes necessary to assess basic chess relationships slow with age, even in experts.     

Multiple meanings,number of related meanings,frequency of occurrence,and the lexicon

A series of experiments was conducted examining lexical access of words with multiple meanings. Words with many meanings were accessed faster than words with few meanings. This effect was obtained independently of word frequency. Furthermore, while words may have several etymological derivations, the number of derivations does not affect access. Finally, among words with an equal number of derivations and an equal number of meanings, those whose meanings tend to be associated with only one derivation are also accessed faster. The relation between number of meanings and word frequency is discussed, especially with respect to the role number of meanings may have played in other research.     

The Model Human Processor and the older adult: parameter estimation and validation within a mobile phone task

The authors estimate weighted mean values for nine information processing parameters for older adults using the Card, Moran, and Newell (1983) Model Human Processor model. The authors validate a subset of these parameters by modeling two mobile phone tasks using two different phones and comparing model predictions to a sample of younger (N = 20; M-sub(age) = 20) and older (N = 20; M-sub(age) = 69) adults. Older adult models fit keystroke-level performance at the aggregate grain of analysis extremely well (R = 0.99) and produced equivalent fits to previously validated younger adult models. Critical path analyses highlighted points of poor design as a function of cognitive workload, hardware/software design, and user characteristics. The findings demonstrate that estimated older adult information processing parameters are valid for modeling purposes, can help designers understand age-related performance using existing interfaces, and may support the development of age-sensitive technologies.