Supplementary Materials – Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

This repository contains supplementary materials for the following journal paper:

Valdemar Švábenský, Brendan Flanagan, Erwin Daniel López Zapata, and Atsushi Shimada.
Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE.
ACM Transactions on Knowledge Discovery from Data (TKDD), 2026.
https://doi.org/10.1145/3798096

Preprint: https://arxiv.org/pdf/2602.17314

@article{Svabensky2026open,
    author    = {\v{S}v\'{a}bensk\'{y}, Valdemar and Flanagan, Brendan and López Zapata, Erwin Daniel and Shimada, Atsushi},
    title     = {{Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE}},
    journal   = {ACM Transactions on Knowledge Discovery from Data (TKDD)},
    publisher = {Association for Computing Machinery},
    year      = {2026},
    volume    = {20},
    number    = {4},
    numpages  = {56},
    issn      = {1556-4681},
    url       = {https://doi.org/10.1145/3798096},
    doi       = {10.1145/3798096},
}

Repository content:

Dataset, code, and additional materials for the paper. See the README.md file in the attached ZIP archive for details.

Attribution (How to cite):

If you use or build upon the materials, please use the BibTeX or full-text citation entry above to cite the source paper.

Contact:

If you notice any issues or breaches of the license terms of this dataset, please contact Valdemar Švábenský using the email address listed in the paper.