L2 lexical decision data

The dataset is used to evaluate the predictive power of different English frequency norms on L2 lexical processing data, which were drawn from the data of an L2 English lexical decision task (Chen et al., 2018) conducted among a group of L2 English learners in China. The dataset presented here includes the L2 mean RT and accuracy data for the 370-word stimuli in Chen et al. (2018), their length (including the number of letters, number of syllables), neighboorhood density scores (OLD), the raw corpus frequencies (KF, CELEX, BNC, COCA, ANC, SUBTLEX-UK, SUBTLEX-US, HAL, USENET, WORLDLEX, WORLDLEX-blog, WORLDLEX-Twitter, WORLDLEX-news, GoogleBooks-AmE, GoogleBooks-BrE), as well as the corresponding Zipf values (see van Heuven et al., 2014), and the subjective frequency ratings collected from L2 English learners in China.

本数据集旨在评估各类英语频率常模对第二语言（L2）词汇加工数据的预测效力，其数据源自一项针对中国L2英语学习者群体开展的L2英语词汇决策任务（Chen等，2018）所采集的数据集。本次发布的数据集包含Chen等（2018）研究中370个词汇刺激项的L2平均反应时（RT）与准确率数据，同时涵盖各刺激项的长度参数（含字母数、音节数）、邻域密度得分（OLD）、原始语料库频率值（包括KF、CELEX、BNC、COCA、ANC、SUBTLEX-UK、SUBTLEX-US、HAL、USENET、WORLDLEX、WORLDLEX-blog、WORLDLEX-Twitter、WORLDLEX-news、GoogleBooks-AmE、GoogleBooks-BrE），以及对应的齐普夫（Zipf）值（详见van Heuven等，2014），此外还包含从中国L2英语学习者群体中采集的主观频率评分。