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.

本数据集旨在评估不同英语频率规范对第二语言词汇处理数据的预测能力，所述数据源自于对中国第二语言英语学习者群体进行的第二语言英语词汇决策任务（Chen 等人，2018年）的数据。该数据集涵盖了 Chen 等人（2018年）中370个词汇的平均反应时间（RT）和准确率数据，包括词汇长度（包括字母数、音节数）、邻域密度评分（OLD）、原始语料库频率（KF、CELEX、BNC、COCA、ANC、SUBTLEX-UK、SUBTLEX-US、HAL、USENET、WORLDLEX、WORLDLEX-blog、WORLDLEX-Twitter、WORLDLEX-news、GoogleBooks-AmE、GoogleBooks-BrE），以及相应的 Zipf 值（参见 van Heuven 等人，2014年），以及从中国第二语言英语学习者收集的主观频率评分。