Department of Linguistics and Languages, McMaster University, Togo Salmon Hall 626, 1280 Main Street West, Hamilton, Ontario, Canada, L8S 4 M2.
Behav Res Methods. 2012 Dec;44(4):978-90. doi: 10.3758/s13428-012-0210-4.
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.
我们提供了 30121 个英语实义词(名词、动词和形容词)的习得年龄(AoA)评级。为了进行数据收集,这项大规模研究使用了亚马逊 Mechanical Turk 提供的基于网络的众包技术。我们的数据表明,以这种方式收集的评级与在实验室条件下收集的评级一样有效和可靠(我们的评级与从美国学生那里在实验室收集的评级之间的相关性对于 2500 个单音节词的子样本达到了.93)。我们还表明,我们的 AoA 评级解释了英语词汇项目词汇判断数据中很大一部分的差异,超过了对数频率、单词长度和与其他单词相似性的影响。这不仅适用于我们评级研究中使用的词干,也适用于它们的屈折形式。我们进一步讨论了 AoA 与其他单词识别预测因素的关系,并说明了 AoA 评级在词汇增长研究中的实用性。