Cluster-Based Performance of Student Dropout Prediction as a Solution for Large Scale Models in a Moodle LMS-Reference-Cited by-同舟云学术

Cluster-Based Performance of Student Dropout Prediction as a Solution for Large Scale Models in a Moodle LMS

Published:2023-03-13 Issue: Volume: Page:
ISSN:
Container-title:LAK23: 13th International Learning Analytics and Knowledge Conference
language:
Short-container-title:

Author:

Poellhuber Louis-Vincent¹^ORCID,Poellhuber Bruno¹^ORCID,Desmarais Michel²^ORCID,Leger Christian¹^ORCID,Roy Normand¹^ORCID,Manh-Chien Vu Mathieu³^ORCID

Affiliation:

1. Universite de Montreal, Canada

2. Polytechnique Montreal, Canada

3. Cegep a distance, Canada

Funder

OBVIA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3576050.3576146

Reference21 articles.

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4. Michel Desmarais and François Lemieux . 2013. Clustering and visualizing study state sequences . In Educational Data Mining 2013 . Michel Desmarais and François Lemieux. 2013. Clustering and visualizing study state sequences. In Educational Data Mining 2013.

5. Xu Du , Juan Yang , Brett E. Shelton , Jui-Long Hung , and Mingyan Zhang . 2021. A systematic meta-review and analysis of learning analytics research. Behaviour & information technology 40, 1 ( 2021 ), 49–62. Xu Du, Juan Yang, Brett E. Shelton, Jui-Long Hung, and Mingyan Zhang. 2021. A systematic meta-review and analysis of learning analytics research. Behaviour & information technology 40, 1 (2021), 49–62.

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