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• Title: Differences in Men's and Women's Knowledge of and Memory for Names (Report)
• Author : North American Journal of Psychology
• Release Date : January 01, 2010
• Genre: Education,Books,Professional & Technical,
• Pages : * pages
• Size : 207 KB

Description

Prior research has shown that words frequently experienced in daily life are responded to faster and remembered better than words infrequently experienced. The word frequency effect has been observed in a variety of tasks. Reading studies have shown that readers spend less time processing high frequency words than low frequency words (Juhasz & Rayner, 2003; Kennison & Clifton, 1995; Rayner & Duffy, 1986). Studies in which participants are instructed to respond to words in isolation have shown that high frequency words are responded to more quickly than low frequency words (Balota & Chumbley, 1985; 1990; Connine, Mullennix, Shernoff, & Yelens, 1990; Howes & Solomon, 1951; Whaley, 1978). In studies requiring participants to remember lists of words, recall performance is generally better for lists containing high frequency words than for lists containing low frequency words (Delosh & McDaniel, 1996; Ward, Woodward, Stevens, & Stinson, 2003; Watkins, LeCompte, & Kim, 2000). Ward et al. (2003) showed that the recall advantage for high frequency words can be explained, at least in part, by the fact that high frequency words receive more rehearsal during study than do low frequency words. Estimates of word frequencies have traditionally been obtained from analyses of printed sources. Frequencies for English words are routinely obtained from the Brown Corpus (Kucera & Francis, 1967; Francis & Kucera, 1982; Marcus, Santorini, & Marcinkiewicz, 1993), which was assembled in the 1960s and contains just over 1 million words. The number of unique words in the corpus is much smaller than 1 million -just over 50,000. Because adult speakers of English may know as many as 80,000 different words (Nagy & Anderson, 1984), there are numerous words that speakers of English know that do not occur at all in the Brown Corpus. Lovelace (1988) pointed out the examples cucumber, lettuce, and toaster. Some researchers (Breland, 1996; Burgess & Livesay, 1998) have argued that word frequency estimates obtained from corpora larger than the Brown Corpus can provide better predictions of processing difficulty for specific words.

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