Dataset Open Access

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

Nioche, Aurélien; Murena, Pierre-Alexandre; de la Torre-Ortiz, Carlos; Oulasvirta, Antti

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).

Files (24.9 MB)
Name Size
data.csv
md5:f8ce8a120b1e7d0886fa8e4bbd7d3c10
9.6 MB Download
data_incl_preliminary_exp.csv
md5:caa4000e5b19f9556b9d19c700224d4b
14.6 MB Download
demographic_info.csv
md5:73b2d33504ad6d61a1ad5811e8a7a7ae
2.2 kB Download
info.ipynb
md5:b908cbd9538814134b02ad7df9c91364
221.7 kB Download
info.pdf
md5:f486e3754b802ef0c7b5ddeaaae62b6e
459.5 kB Download
stimuli.csv
md5:85a39f70a13b6e47f82e8f77dd9913f6
23.2 kB Download
  • Aurelien Nioche, Pierre-Alexandre Murena, Carlos de la Torre-Ortiz, and Antti Oulasvirta. 2021. Improving Artificial Teachers by Considering How People Learn and Forget. In 26th International Conference on Intelligent User Interfaces (IUI '21). Association for Computing Machinery, New York, NY, USA, 445–453. DOI:https://doi.org/10.1145/3397481.3450696

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