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.