358,534 nonwords: The ARC Nonword Database

Rastle, Kathleen; Harrington, Jonathan; Coltheart, Max

doi:10.1080/02724980244000099

Cited by 435 publications

(323 citation statements)

References 39 publications

(53 reference statements)

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“…Nonwords were compiled using the ARC nonword database (www.maccs.mq.edu.au/~nwdb/nwdb. html; Rastle, Harrington, & Coltheart, 2002). Nonwords were 4-8 letters long and matched with the words on letter length frequency.…”

Section: Methodsmentioning

confidence: 99%

Source-constrained retrieval influences the encoding of new information

2011

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Jacoby, Shimizu, Daniels, and Rhodes (Psychonomic Bulletin & Review, 12, 852-857, 2005) showed that new words presented as foils among a list of old words that had been deeply encoded were themselves subsequently better recognized than new words presented as foils among a list of old words that had been shallowly encoded. In Experiment 1, by substituting a deep-versus-shallow imagery manipulation for the levels-of-processing manipulation, we demonstrated that the effect is robust and that it generalizes, also occurring with a different type of encoding. In Experiment 2, we provided more direct evidence for context-related encoding during tests of deeply encoded words, showing enhanced priming for foils presented among deeply encoded targets when participants made the same deep-encoding judgments on those items as had been made on the targets during study. In Experiment 3, we established that the findings from Experiment 2 are restricted to this specific deep judgment task and are not a general consequence of these foils being associated with deeply encoded items. These findings provide support for the sourceconstrained retrieval hypothesis of Jacoby, Shimizu, Daniels, and Rhodes: New information can be influenced by how surrounding items are encoded and retrieved, as long as the surrounding items recruit a coherent mode of processing.

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Section: Methodsmentioning

confidence: 99%

Source-constrained retrieval influences the encoding of new information

2011

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“…They must make sure that there are no systematic differences between the words and the nonwords, other than the fact that the former belong to the language and the latter do not (see Rastle, Harrington, & Coltheart, 2002, for a similar message). This requirement is particularly relevant when the number of trials is large and participants have the time to tune in to any bias in the stimulus materials.…”

Section: Limitations Of the Available Solutionsmentioning

confidence: 99%

“…The traditional method to generate pseudowords, as was used to fill the ARC nonword database (Rastle et al, 2002), is based on combining subsyllabic elements that are legal in the language of choice. A conventional way to describe a syllable is to divide it into onset, nucleus, and coda.…”

Section: The Wuggy Algorithmmentioning

confidence: 99%

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Wuggy: A multilingual pseudoword generator

Keuleers

Brysbaert

2010

Behavior Research Methods

563

409

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Nonwords are essential in lexical decision tasks in which participants are confronted with strings of letters or sounds and have to decide whether the stimulus forms an existing word. Together with word naming, semantic classification, perceptual identification, and eye-movement tracking during reading, the lexical decision task is one of the core instruments in the psycholinguist's toolbox for the study of word processing.Although researchers are concerned particularly with the quality of their word stimuli (because their investigation depends on them), there is plenty of evidence that the nature of the nonwords also has a strong impact on lexical decision performance. As a rule, the more dissimilar the nonwords are to the words, the faster are the lexical decision times and the smaller is the impact of word features such as word frequency, age of acquisition, and spelling-sound consistency (e.g., Borowsky & Masson, 1996;Gerhand & Barry, 1999;Ghyselinck, Lewis, & Brysbaert, 2004;Gibbs & Van Orden, 1998). For instance, in Gibbs and Van Orden (Experiment 1), lexical decision times to the words were shortest (496 msec) when the nonwords were illegal letter strings (i.e., letter sequences, such as ldfa, that are not observed in the language), longer (558 msec) when the nonwords were legal letter strings (e.g., dilt), and still longer (698 msec) when the nonwords were pseudohomophones (i.e., sounding like real words, e.g., durt). At the same time, the difference in reaction times (RTs) between words with a consistent rhyme pronunciation (e.g., beech) and matched words with an inconsistent rhyme pronunciation (e.g., beard [inconsistent with heard]) increased. Because of the impact of the nonwords on lexical decision performance, there is general agreement among researchers that nonwords should be legal nonwords, unless there are theoretical reasons to use illegal nonwords. Legal nonwords that conform to the orthographic and phonological patterns of a language are also called pseudowords.Although the requirement of pseudowords solves many problems for the creation of nonwords in the lexical decision task, there are additional considerations that must be taken into account. Because lexical decision is, in essence, a signal detection task (e.g., Ratcliff, Gomez, & McKoon, 2004), participants in a lexical decision task not only base their decision on whether the stimuli belong to the language, they also rely on other cues that help to differentiate between the word and nonword stimuli. In the same way that participants learn ties in apparently random materials generated on the basis of an underlying grammar (i.e., the phenomenon of implicit learning; Reber, 1989), so are participants susceptible to systematic differences between the word trials (requiring a "yes" response) and the nonword trials (requiring a "no" response). They exploit these biases to optimize their responses. Chumbley and Balota's (1984) study provides an example of this process. Because of an oversight, in their Experiment 2, the nonwords were on aver...

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“…In the mixed version, the 168 non-words comprised 140 English-sounding pseudohomophones selected from Rodd (2000) and the ARC non-word and pseudohomophone database (Rastle, Harrington, & Coltheart, 2002), as well as 28 Dutch words (e.g. "vijand") of a similar frequency to the target items, selected pseudorandomly from the SUBTLEX-NL database.…”

Section: Non-wordsmentioning

confidence: 99%

The cognate facilitation effect in bilingual lexical decision is influenced by stimulus list composition

Poort

Rodd

2017

Acta Psychologica

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Cognates share their form and meaning across languages: "winter" in English means the same as "winter" in Dutch. Research has shown that bilinguals process cognates more quickly than words that exist in one language only (e.g. "ant" in English). This finding is taken as strong evidence for the claim that bilinguals have one integrated lexicon and that lexical access is language nonselective. Two English lexical decision experiments with DutchEnglish bilinguals investigated whether the cognate facilitation effect is influenced by stimulus list composition. In Experiment 1, the 'standard' version, which included only cognates, English control words and regular nonwords, showed significant cognate facilitation (31 ms). In contrast, the 'mixed' version, which also included interlingual homographs, pseudohomophones (instead of regular non-words) and Dutchonly words, showed a significantly different profile: a non-significant disadvantage for the cognates (8 ms). Experiment 2 examined the specific impact of these three additional stimuli types and found that only the inclusion of Dutch words significantly reduced the cognate facilitation effect. Additional exploratory analyses revealed that, when the preceding trial was a Dutch word, cognates were recognised up to 50 ms more slowly than English controls. We suggest that when participants must respond 'no' to non-target language words, competition arises between the 'yes'-and 'no'-responses associated with the two interpretations of a cognate, which cancels out the facilitation that is a result of the cognate's shared form and meaning. We conclude that the cognate facilitation effect is a real effect that originates in the lexicon, but that cognates can be subject to competition effects outside the lexicon.

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358,534 nonwords: The ARC Nonword Database

Cited by 435 publications

References 39 publications

Source-constrained retrieval influences the encoding of new information

Source-constrained retrieval influences the encoding of new information

Wuggy: A multilingual pseudoword generator

The cognate facilitation effect in bilingual lexical decision is influenced by stimulus list composition

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