BOUSFIELD 1953 PDF

of Clustering in the Recall of Randomly Arranged Associates · W. A. Bousfield et al. The Journal of Psychology. Volume 36, – Issue 1. Bousfield, W.A. BousfieldThe occurrence of clustering in the recall of randomly arranged associates. Journal of General Psychology, 49 (), pp. Psychol., 49 (), pp. Google Scholar. Bousfield et al., W.A. Bousfield, B.H. Cohen, G.A. WhitmarshAssociative clustering in the recall of words.

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Suppose the simulated participant has just bouzfield a list of n words. Predicting human brain activity associated with the meanings of nouns. We then create a pool of the n – 1 remaining words from the studied list. If one observes or fails to observe a similar pattern of clustering scores across experimental conditions when using multiple semantic similarity models e.

Each dot corresponds to a single comparison between two words. Author information Copyright and License information Disclaimer.

Interpreting semantic clustering effects in free recall

Clustering in free recall as a function of certain methodological variations. For each participant we also constructed 50 lists of 15 unique items each, drawn from the word pool. Two measures of semantic similarity A. Discussion Our simulations yield four valuable insights into the interpretation of semantic clustering during free recall. Our simulations yield four valuable insights into the interpretation of semantic clustering during free recall.

Interpreting semantic clustering effects in free recall.

Given that the clustering scores obtained using any given model of semantic bouscield are likely to be only noisy reflections of any true patterns in the data, one should use multiple models of semantic similarity whenever possible. We then computed the similarity between each pair of words by boisfield the cosine of the angle between the corresponding LSA vectors.

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Rather, a near-ceiling clustering score may reflect the specific sequence of words presented to the participant, or the specific structure of the experiment. We order the words in the pool by their semantic similarity according to g p to i 1.

Acquisition, storage, and retrieval in digital and biological brains. See other articles in PMC that cite the published article.

Interpreting semantic clustering effects in free recall.

Distribution of the pairwise WAS-derived semantic similarity values for the same words. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall. Analysis Our simulations are intended to estimate the maximum expected magnitude of semantic clustering effects in free recall. We expect that these biases are related to the form of the semantic similarity distributions derived from each measure see Bousfiels.

Footnotes bousfirld Here the functions f and g p are mappings from two words, a and bonto scalar similarity values.

In the present manuscript we use simulations to study these questions. For example, the recency and primacy effects refer to the well-established tendency of participants to show superior recall of items from the ends, and to a lesser extent, from the beginnings of the studied lists Deese and Kaufman, ; Murdock, Our simulations are intended to estimate the maximum expected magnitude of semantic clustering effects in free recall.

The free recall paradigm has participants study lists of items — typically words — and subsequently recall the studied items in the order they come to mind. There is some evidence that similarities in the neural patterns evoked by thinking about a given pair of words predict the tendencies of participants to successively recall the words, given that both appeared on the studied lists Manning, We begin by selecting the first recalled word, i 1at random from bojsfield set of n studied words.

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We also found that the semantic clustering scores computed using LSA were slightly but reliably higher than those computed using WAS paired t -test: Specifically, we calculate the proportion of the possible similarity values that the observed value is greater than, since strong semantic clustering will cause the observed similarity values to be larger than average.

The binning reveals an approximately monotonic relation between the two similarity measures. In theory, one could estimate g p for a given participant by having the participant make judgements about the semantic similarities between each pair of studied words.

Using fMRI brain activation to identify cognitive states associated with perception of tools 153 dwellings. Serial effects in recall of unorganized and sequentially organized verbal material.

Theta and gamma oscillations during encoding predict subsequent recall. The serial position effect of free recall.

Predicting clustering from semantic structure. Semantic clustering score The semantic clustering score, developed by Polyn et al. We first divided the distributions of LSA-derived pairwise similarity values into equally sized bins the centers of the bins are plotted along the x -coordinate.

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