Accounting for item-level variance in recognition memory: Comparing word frequency and contextual diversity

Author(s):  
Brendan T. Johns
Memory ◽  
1994 ◽  
Vol 2 (3) ◽  
pp. 255-273 ◽  
Author(s):  
Robert E. Guttentag ◽  
Donna Carroll

1970 ◽  
Vol 83 (3) ◽  
pp. 343 ◽  
Author(s):  
Benton J. Underwood ◽  
Joel S. Freund

2018 ◽  
Vol 71 (10) ◽  
pp. 2207-2222 ◽  
Author(s):  
Mabel C Lau ◽  
Winston D Goh ◽  
Melvin J Yap

Psycholinguists have developed a number of measures to tap different aspects of a word’s semantic representation. The influence of these measures on lexical processing has collectively been described as semantic richness effects. However, the effects of these word properties on memory are currently not well understood. This study examines the relative contributions of lexical and semantic variables in free recall and recognition memory at the item-level, using a megastudy approach. Hierarchical regression of recall and recognition performance on a number of lexical-semantic variables showed task-general effects where the structural component, frequency, number of senses, and arousal accounted for unique variance in both free recall and recognition memory. Task-specific effects included number of features, imageability, and body–object interaction, which accounted for unique variance in recall, whereas age of acquisition, familiarity, and extremity of valence accounted for unique variance in recognition. Forward selection regression analyses generally converged on these findings. Hierarchical regression also revealed that lexical variables accounted for more variance in recognition compared with recall, whereas semantic variables accounted for more unique variance above and beyond lexical variables in recall compared with recognition. Implications of the findings are discussed.


2005 ◽  
Vol 24 (3) ◽  
pp. 587-598 ◽  
Author(s):  
Greig I. de Zubicaray ◽  
Katie L. McMahon ◽  
Matthew M. Eastburn ◽  
Simon Finnigan ◽  
Michael S. Humphreys

2012 ◽  
Vol 132 (2) ◽  
pp. EL74-EL80 ◽  
Author(s):  
Brendan T. Johns ◽  
Thomas M. Gruenenfelder ◽  
David B. Pisoni ◽  
Michael N. Jones

2011 ◽  
Vol 52 (6) ◽  
pp. 516-523 ◽  
Author(s):  
CLELIA ROSSI-ARNAUD ◽  
LAURA PIERONI ◽  
PIETRO SPATARO ◽  
VINCENZO CESTARI

2013 ◽  
Vol 35 (4) ◽  
pp. 727-755 ◽  
Author(s):  
Scott A. Crossley ◽  
Nicholas Subtirelu ◽  
Tom Salsbury

This study examines frequency, contextual diversity, and contextual distinctiveness effects in predicting produced versus not-produced frequent nouns and verbs by early second language (L2) learners of English. The study analyzes whether word frequency is the strongest predictor of early L2 word production independent of contextual diversity and distinctiveness and whether differences exist in the lexical properties of nouns and verbs that can help explain beginning-level L2 word production. The study uses machine learning algorithms to develop models that predict produced and unproduced words in L2 oral discourse. The results demonstrate that word frequency is the strongest classifier of whether a noun is produced or not produced in beginning L2 oral discourse, whereas contextual diversity is the strongest classifier of whether a verb is produced or not produced. Post hoc tests reveal that nouns are more concrete, meaningful, imageable, specific, and unambiguous than verbs, which indicates that lexical properties may explain differences in noun and verb production. Thus, whereas distributional properties of nouns may allow lexical acquisition on the basis of association through exposure alone (i.e., nouns may adhere to frequency effects), the abstractness and ambiguity found in verbs make them difficult to acquire based solely on repetition. Therefore, verb acquisition may follow a principle of likely need characterized by contextual diversity effects.


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