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In this paper, we consider the different methods that have been developed to quantify random generation behavior and incorporate these measurement scales into a Windows95 computer program called RgCalc. RgCalc analyzes the quality of human attempts at random generation and can provide computer-generated, pseudorandom sequences for comparison. The program is designed to be appropriate for the analysis of various types of random generation situations employed in the psychological literature. The different algorithms for the evaluation of a dataset are detailed and an outline of the program is described. Performance measures are available for assessing various aspects of the response distribution, the sequencing of pairs, the ordinal relationships between sets of items, and the tendency to repeat alternatives over different lengths. A factor analysis is used to illustrate the multiple dimensions underlying human randomization processes. MEASURES OF RANDOMIZATION PERFORMANCE Redundancy In terms of classic information theory analyses (Attneave, 1959; Shannon & Weaver, 1949), a sequence of items can be said to contain maximum first-order infor-583

This paper considers working memory capacity, critically examining the hypothesis that counting span (the ability to count arrays of objects and store count totals) reflects a trade-off in resources available for processing and short-term storage. Previous evidence interpreted as favouring this hypothesis has confounded task difficulty with counting time. Experiment 1 validated a manipulation of the attentional demands of counting in which target objects were differentiated from non-targets by either a single feature (colour) or a feature conjunction (a combination of line orientations). The results confirmed that the two presentations involved qualitatively different attentional loads. Experiment 2 used these displays to compare counting span for children aged 6 to 11, both with and without an adjustment of target numerosity to control for differences in processing time. At all ages, span was lower when counting took longer, but there was no difference between feature and conjunction arrays once counting time was accounted for. These results argue against a resource trade-off interpretation of counting span. Rather, they support a hypothesis of resource-switching among children, implying that counting span acts as a measure of time-based forgetting.

Explanations of working memory span in children were studied in a longitudinal follow-up of J. N. Towse, G. J. Hitch, and U. Hutton (1998). Reading span and operation span were lower when within-task retention intervals were lengthened. For each task, variation in span between test waves and age cohorts was systematically related to changes in processing speed. The two spans explained substantial shared variance in both reading and arithmetic scores, with some evidence for domain specificity. Combined span scores predicted unique variance in scholastic attainment over a 1-year interval. The authors concluded that working memory span is constrained by rapid loss of active codes and is not simply a measure of capacity for resource sharing. Working memory is also implicated in scholastic development.

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