L2 lexical decision data

Published: 2 April 2019| Version 1 | DOI: 10.17632/yzzfp97m92.1
Contributor:
Xiaocong Chen

Description

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.

Files

Categories

Linguistics, Psycholinguistics

License