Practice Effects in Large-Scale Visual Word Recognition Studies: A Lexical Decision Study on 14,000 Dutch Mono- and Disyllabic Words and Nonwords

Abstract

In recent years, psycholinguistics has seen a remarkable growth of research based on the analysis of data from large-scale studies of word recognition, in particular lexical decision and word naming. We present the data of the Dutch Lexicon Project (DLP) in which a group of 39 participants made lexical decisions to 14,000 words and the same number of nonwords. To examine whether the extensive practice precludes comparison with the traditional short experiments, we look at the differences between the first and the last session, compare the results with the English Lexicon Project (ELP) and the French Lexicon Project (FLP), and examine to what extent established findings in Dutch psycholinguistics can be replicated in virtual experiments. Our results show that when good nonwords are used, practice effects are minimal in lexical decision experiments and do not invalidate the behavioral data. For instance, the word frequency curve is the same in DLP as in ELP and FLP. Also, the Dutch–English cognate effect is the same in DLP as in a previously published factorial experiment. This means that large-scale word recognition studies can make use of psychophysical and psychometrical approaches. In addition, our data represent an important collection of very long series of individual reaction times that may be of interest to researchers in other areas.

The processing of singular and plural nouns in English, French, and Dutch: New insights from megastudies.

“…This is also in line with the strong nonlinearity of the frequency effect (Baayen, 2005;Baayen et al, 2006;Balota et al, 2004;Keuleers, Diependaele et al, 2010) and the observation that the frequency effect is much weaker for high than for low-frequency word forms. However, the tendency in the three languages was in favour of the surface frequency for the plural form (as can be seen with the R 2 values), as predicted by the PDR and Taft models (but this is speculation).…”

How strongly do word reading times and lexical decision times correlate? Combining data from eye movement corpora and megastudies

“…Second, for lexical decision and word naming, but not for word reading data, the frequency effect levels off for frequencies above 50 pm (log = 1.7). The floor effect for high frequencies in the lexical decision task has been reported before by other authors (Balota et al, 2004;Baayen et al, 2006;Ferrand et al, 2010;Keuleers, Diependaele, & Brysbaert, 2010b;Keuleers, Lacey, Rastle, & Brysbaert, in press). …”

Procura-PALavras (P-Pal): uma nova medida de frequência lexical do português europeu contemporâneo

“…Em todo o caso, à semelhança de vários projectos internacionais (ex., English Lexicon Project -ver Balota et al, 2007), estudos futuros deverão comprovar a qualidade desta medida a partir, por exemplo, da recolha de tempos de reconhecimento e/ou nomeação de um vasto conjunto de palavras com vista à determinação do seu poder preditivo. Estudos deste tipo são tanto mais relevantes quanto a investigação internacional mais recente comprova, como vimos, que a frequência de uso de palavras se assume como a variável mais potente na explicação do desempenho linguístico dos sujeitos (ex., Balota et al, 2007;Brysbaert & Cortese, 2011;Ferrand et al, 2010;Keuleers et al, 2010;Thompson & Desroches, 2009).…”

“…A sua extracção a partir de corpora de menores dimensões pode subestimar a ocorrência das palavras, especialmente as de baixa frequência. Esta situação é tanto mais relevante quanto os trabalhos recentes levados a cabo no âmbito do English Lexicon Project (Balota et al, 2007), do French Lexicon Project (Ferrand et al, 2010) e do Dutch Lexicon Project (Keuleers, Diependaele, & Brysbaert, 2010) revelarem que a quase totalidade do efeito de frequência se situa nos intervalos de frequência abaixo das 10 ocorrências por milhão de palavras. Além disso, como refere Lee (2003), de um ponto de vista estatístico, a extracção de frequências é mais adequada a partir de grandes amostras porque o erro padrão de medida varia em função da raiz quadrada do tamanho da amostra.…”