This repository contains data analysis for the experiment we conducted for the research on how the perceptual load may affect programming performance in people with symptoms of ADHD. Developers filled in the Barkley's Scale, which indicates the presence and severity levels of ADHD symptoms. After that, participants solved mentally active programming tasks (coding) and monotonous ones (debugging) in the PyCharm IDE. Each task were present in high perceptual load modes (visually noisy) and low perceptual load modes (visually clear).

The data was collected with the plugin that tracks efficiency metrics, i.e. time, speed, and activity.

We found that the perceptual load does affect programmers’ efficiency. Our findings support the idea of behavioral assessment of users for providing accommodation for the workforce with special needs.

For more details please refer to the paper: The Effect of Perceptual Load on Performance within IDE in People with ADHD Symptoms

All requirements are listed in pyproject.toml. Use poetry to create environment.

poetry install

The raw data collected by plugin located at sources directory.

Go to processing.ipynb and run the code. You can place raw data in different location, just make sure to edit data path in the first chunk of processing.ipynb.

USER_PATH = 'sources'

The code should construct dataset for the analysis and save it to data directory.

Data analysis is done in post_processing.ipynb. You can run the notebook cell by cell from the beginning or use 'run all' button in the IDE to recreate the complete analysis.

The main results of the paper support the idea that level of perceptual load does affect people with and without ADHD related symptoms differently.

This project was made in Machine Learning for Software Engineering Research Group in JetBrains Research.

Supervisor and contributor of this project is Sergey Titov

Authors: Vseslav Kasatskii, Agnia Serheyuk, Anastasiia Serova, Sergey Titov