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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Predicting clustering from semantic structure. We have focused on a single semantic clustering metric, the semantic clustering score Polyn et al. Bousfie,d that the clustering scores obtained using any given model of semantic similarity are likely to be only noisy reflections of any true patterns in the data, one should use multiple models of semantic similarity whenever possible. For example, the recency and primacy effects refer to the well-established tendency of participants to show superior 11953 of items from the ends, and to a lesser extent, from the beginnings of the studied lists Deese and Kaufman, ; Murdock, Analysis Our simulations are intended to estimate the maximum expected magnitude of semantic clustering effects in free recall.

Interpreting semantic clustering effects in free recall.

We ran two batches of simulations. This indicates that different semantic similarity metrics used in analyses of semantic clustering may introduce slight biases. Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning.

An analysis of sequences of restricted associative responses. We next generate a percentile score by comparing the semantic similarity value corresponding bouafield the next item in the recall sequence with the rest of the distribution. Rather, we simply found the semantic clustering score toprovide a convenient means of quantifying semantic clustering. In theory, one could estimate g p for a given participant by having the participant make judgements about the semantic similarities between bousfkeld pair of studied words.


Author information Copyright and License information Disclaimer. Serial effects in recall of unorganized and sequentially organized verbal material. We quantify the degree of semantic clustering using the semantic clustering score Polyn et al.

When there is a tie, we score this as the percentile falling halfway between the two items. Clustering in free recall as a function of certain methodological variations. However, the techniques developed here are equally applicable to arbitrary choices of n and k. Word association spaces for predicting semantic similarity effects in episodic memory. The Google similarity distance. Generating recall sequences that maximize the semantic clustering score As defined above, the semantic clustering score according to metric g p is maximized i.

In particular, how should the magnitudes of semantic clustering effects be interpreted?

Interpreting semantic clustering effects in free recall

In addition to ordering recalls by the study positions of the items, participants also exhibit striking effects of semantic clustering Bousfield and Sedgewick, ; Jenkins and Russell, ; Bousfield, ; Cofer et al. In this way, if a participant always chose the closest semantic associate, then their semantic clustering score would be 1.

Each dot corresponds to a single comparison between two words.

The semantic clustering score must bousfielc computed independently for each studied list. This word pool has been used in several published free recall studies Sederberg et al. This shows that even participants who exhibit strong semantic clustering may still show clustering scores near 0. National Center for Biotechnology InformationU. Associative clustering during recall.


Abstract The order in which participants choose to recall words from a studied list of randomly selected words provides insights 1935 how memories of the words are represented, organized, and retrieved. We then measure the degree of semantic clustering according to a different similarity metric, f. Results We ran two batches of simulations. Specifically, 19553 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.

Discussion Our simulations yield four valuable insights into the interpretation of semantic clustering bousfieod free recall. Although the similarity values produced by each of these myriad similarity metrics are somewhat related, the pairwise correlations between the measures tend to be surprisingly low.

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, bousfkeld that both appeared on the studied lists Manning, We order the words in the pool by their semantic similarity according to g p to i 1.

Journal of Experimental Psychology. Predicting human brain activity associated with the meanings of nouns. We used the set of pairwise similarities for this set of highly imageable nouns in our bousfieeld. Cognitive Psychology and its Applications: As described below, the recall sequences are constructed to maximize semantic clustering according to g p for each participant.

As defined above, the semantic clustering score according to metric g p is maximized i.