We present age-of-acquisition (AoA) ratings for 30,121 English content words (nouns, verbs, and adjectives). For data collection, this megastudy used the Web-based crowdsourcing technology offered by the Amazon Mechanical Turk. Our data indicate that the ratings collected in this way are as valid and reliable as those collected in laboratory conditions (the correlation between our ratings and those collected in the lab from U.S. students reached .93 for a subsample of 2,500 monosyllabic words). We also show that our AoA ratings explain a substantial percentage of the variance in the lexical-decision data of the English Lexicon Project, over and above the effects of log frequency, word length, and similarity to other words. This is true not only for the lemmas used in our rating study, but also for their inflected forms. We further discuss the relationships of AoA with other predictors of word recognition and illustrate the utility of AoA ratings for research on vocabulary growth.
Keywords Word recognition . Age of acquisition . Ratings . Amazon Mechanical TurkResearchers using words as stimulus materials typically control or manipulate their stimuli on a number of variables.The four that are most commonly used are word frequency, word length, similarity to other words, and word onset. In this article, we will argue that age of acquisition (AoA) should be part of this list, and we provide ratings for a substantial number of words in order to do so. First, however, we will discuss the evidence in favor of the big four.