This repository contains the code for all experiments described in the following paper:
Modeling Student Response Times: Towards Efficient One-on-one Tutoring Dialogues
Luciana Benotti, Jayadev Bhaskaran, Sigtryggur Kjartansson, David Lang
EMNLP Workshop on Noisy User Generated Text (W-NUT) at EMNLP 2018, Brussels, Belgium.
The paper can be found here.
- Create a virtual environment called
rt
:
conda create -n rt python=3.6 anaconda
To enter the environment run
source activate rt
To exit the environment run
source deactivate rt
- Enter the newly created virtual environment
- Install package requirements
pip install -r requirements.txt
- Install package
python setup.py install
Note: You will have to repeat steps 3. and 4. throughout development as we add new dependencies and modules.
- requirements.txt - make sure to update this file every time you add a new import!
- data/ - directory that will contain all data.
- runs/ - directory to store training run outputs.
- src/ - directory for all source code (e.g. models, trainers, analysis scripts etc.)
- src/config.py - central location for any project structure constants (e.g. paths to data). This is not intended for model parameters.