Improving Artificial Teachers by Considering How People Learn and Forget: Dataset

  • Aurélien Nioche (Creator)
  • Pierre-Alexandre Murena (Creator)
  • Carlos de la Torre-Ortiz (Creator)
  • Antti Oulasvirta (Creator)



This dataset contains the results of the experiment described in Nioche et al. (2021).

This dataset contains 4 data files:

data.csv: the main data file.
stimuli.csv: the description/listing of the stimuli.
demographic_info.csv: the demographic information about the users.
data_incl_preliminary_exp.csv: an additional data file that includes the user of the preliminary experiments
The main data file contains the logs of 53 different users using a self-teaching application for one week. The goal of the users was to learn the English meaning of Japanese kanji. Each user completed between 1370 trials and 1608 trials. Each user saw between 85 and 204 characters.

Two additional files are also joint to the data files:

info.ipynb: A Jupyter notebook that provides information about each data file, a few descriptive plots, and an example of data manipulation.
info.pdf: A pdf rendering of the notebook.
If you use this dataset, please refer to it by citing Nioche et al. (2021).
Date made available2021

Dataset Licences

  • CC-BY-4.0
  • Improving Artificial Teachers by Considering How People Learn and Forget

    Nioche, A., Murena, P-A., de la Torre Ortiz, C. & Oulasvirta, A., 14 Apr 2021, 26th International Conference on Intelligent User Interfaces, IUI 2021. ACM, p. 445-453 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Open Access
    5 Citations (Scopus)
    131 Downloads (Pure)

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