An in-depth methodology to predict at-risk learners

Amal Ben Soussia, Azim Roussanaly, Anne Boyer

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DOI: 10.1007/978-3-030-86436-1_15
Published: 2021-09-20
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Publisher: Springer Cham
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1007/978-3-030-86436-1_15,
  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}
}

RIS

TY  - JOUR
TI  - An in-depth methodology to predict at-risk learners
AU  - Amal Ben Soussia
AU  - Azim Roussanaly
AU  - Anne Boyer
PY  - 2021
DO  - 10.1007/978-3-030-86436-1_15
UR  - https://doi.org/10.1007/978-3-030-86436-1_15
ER  -

APA

Soussia, A. B., Roussanaly, A., & Boyer, A. (2021). An in-depth methodology to predict at-risk learners. https://doi.org/10.1007/978-3-030-86436-1_15

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hal · retrieved 2026-11-10T12:23:50.110Z