title: Models of verbal working memory capacity: what does it take to make them work?
abstract: Theories of working memory (WM) capacity limits will be more useful when we know what aspects of performance are governed by the limits and what aspects are governed by other memory mechanisms. Whereas considerable progress has been made on models of WM capacity limits for visual arrays of separate objects, less progress has been made in understanding verbal materials, especially when words are mentally combined to form multiword units or chunks. Toward a more comprehensive theory of capacity limits, we examined models of forced-choice recognition of words within printed lists, using materials designed to produce multiword chunks in memory (e.g., leather brief case). Several simple models were tested against data from a variety of list lengths and potential chunk sizes, with test conditions that only imperfectly elicited the interword associations. According to the most successful model, participants retained about 3 chunks on average in a capacity-limited region of WM, with some chunks being only subsets of the presented associative information (e.g., leather brief case retained with leather as one chunk and brief case as another). The addition to the model of an activated long-term memory component unlimited in capacity was needed. A fixed-capacity limit appears critical to account for immediate verbal recognition and other forms of WM. We advance a model-based approach that allows capacity to be assessed despite other important processing contributions. Starting with a psychological-process model of WM capacity developed to understand visual arrays, we arrive at a more unified and complete model.
authors.affiliation: Department of Psychological Sciences, University of Missouri, 18 McAlester Hall, Columbia, MO 65211, USA. CowanN@missouri.edu
authors.forename: Nelson
authors.initials: N
authors.lastname: Cowan
authors.forename: Jeffrey N
authors.initials: JN
authors.lastname: Rouder
authors.forename: Christopher L
authors.initials: CL
authors.lastname: Blume
authors.forename: J Scott
authors.initials: JS
authors.lastname: Saults
mesh_terms: D000293:Adolescent; D000704:Analysis of Variance; D001245:Association Learning / Q000502:physiology*; D001288:Attention; D001499:Bayes Theorem; D003463:Cues; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008570:Memory, Short-Term / Q000502:physiology*; D008960:Models, Psychological; D009483:Neuropsychological Tests / Q000706:statistics & numerical data*; D010775:Photic Stimulation; D021641:Recognition, Psychology; D055815:Young Adult