This project contains data and code for our project on learning of morphological paradigms. Experiment Scripts contains e-prime 2.0 (Professional) scripts and editable e-studio files for the experiments Code contains computational modeling code. The learning model itself is in RescorlaFunction.R, where Rescorla() is the function to source. RescorlaSimulation_Morphology.R examines the fit of the model in predicting the choice of suffix in our data, varying salience parameters described in the paper. The output of this script is in Modeling Results > ndl_SufChoice... files. There is one file for each Order x Language combination. RescorlaSimulation_Phonology.R examines the fit of the model in predicting the choice of suffix in our data, varying salience parameters described in the paper. The output of this script is in Modeling Results > ndl_Pal... files findBestModelPars.R takes in the data generated by these two functions to identify the best salience parameters overall and for each training Order condition This script generated pal.pars.txt and suf.pars.txt in Modeling Results Data folder contains the empirical data. ProductionAnalysis.R contains the script for performing the inferential statistical analyses in the paper