Amal Ben Soussia, Azim Roussanaly, Anne Boyer. An In-Depth Methodology to Predict At-Risk Learners. In Tinne De Laet, Roland Klemke, Carlos Alario-Hoyos, Isabel Hilliger, Alejandro Ortega-Arranz, editors, Technology-Enhanced Learning for a Free, Safe, and Sustainable World - 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, Bolzano, Italy, September 20-24, 2021, Proceedings. Volume 12884 of Lecture Notes in Computer Science, pages 193-206, Springer, 2021. [doi]
@inproceedings{SoussiaRB21,
title = {An In-Depth Methodology to Predict At-Risk Learners},
author = {Amal Ben Soussia and Azim Roussanaly and Anne Boyer},
year = {2021},
doi = {10.1007/978-3-030-86436-1_15},
url = {https://doi.org/10.1007/978-3-030-86436-1_15},
researchr = {https://researchr.org/publication/SoussiaRB21},
cites = {0},
citedby = {0},
pages = {193-206},
booktitle = {Technology-Enhanced Learning for a Free, Safe, and Sustainable World - 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, Bolzano, Italy, September 20-24, 2021, Proceedings},
editor = {Tinne De Laet and Roland Klemke and Carlos Alario-Hoyos and Isabel Hilliger and Alejandro Ortega-Arranz},
volume = {12884},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-86436-1},
}