nickduran / dynamical-NNS-passive

Code for preparing and analyzing complete dataset for replicating results reported in "The Action Dynamics of Native and Non-native Speakers of English in Processing Active and Passive Sentences" (Crossley, Duran, Kim, Lester, & Clark, 2018; Linguistic Approaches to Bilingualism). Code written in Python, Matlab, and R.

The Action Dynamics of Native and Non-native Speakers of English in Processing Active and Passive Sentences (Linguistic Approaches to Bilingualism)

• Step 1: Prepare raw x,y trajectories from MouseTracker for variable extraction. Code written in Python.
• Step 2: Extract action dynamics variables as reported in paper. Code written in Matlab.
• Step 3: Generate statistical models for replicating results reported in paper. Code written in R.
• Also included are TOEFL scores for each participant and various R helper functions for generating statistical models.

Raw data

all_mt_files

Step 1: Prepare raw data to generate DVs

masterPrepPassives.ipynb

Step 2: Generate action dynamics DVs

extractDVs.m

Step 3: Run statistical models

activePassive_analysis.Rmd

Additional files

• TOEFLSCORES.csv

  TOEFL scores for NNS participants

• save_model.R

  Helper functions for reporting analyses