Item strength affects working memory capacity
Do the processing and online manipulation of stimuli that are less familiar require more working memory (WM) resources? Is it more difficult to solve demanding problems when the symbols involved are less rather than more familiar? We explored these questions with a dual-task paradigm in which subjects had to solve algebra problems of different complexities while simultaneously holding novel symbol–digit associations in WM. The symbols were previously unknown Chinese characters, whose familiarity was manipulated by differential training frequency with a visual search task for nine hour-long sessions over 3 weeks. Subsequently, subjects solved equations that required one or two transformations. Before each trial, two different integers were assigned to two different Chinese characters of the same training frequency. Half of the time, those characters were present as variables in the equation and had to be substituted for the corresponding digits. After attempting to solve the equation, subjects had to recognize which two characters were shown immediately before that trial and to recall the integer associated with each. Solution accuracy and response times were better when the problems required one transformation only; variable substitution was not required; or the Chinese characters were high frequency. The effects of stimulus familiarity increased as the WM demands of the equation increased. Character–digit associations were also recalled less well with low-frequency characters. These results provide strong support that WM capacity depends not only on the number of chunks of information one is attempting to process but also on their strength or familiarity.
KeywordsWorking memory Familiarity Knowledge Math Problem-solving
L.R. developed the theory, idea for the study, and design. Z.S. provided the program to collect the data and collected the data. V.P. found a design bug and fixed it. Z.S. analyzed the data under V.P.’s supervision. Everyone contributed to the writing of this article, with V.P. making by far the largest contribution.
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