GA-TabNet: a novel approach for early dropout prediction in MOOCs based on genetic algorithms and TabNet

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Authors

Publication Details

Journal
International Journal of Business Intelligence and Data Mining
Published
2025-09-16
DOI
https://doi.org/10.1504/ijbidm.2026.10073518
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

GA-TabNet: a novel approach for early dropout prediction in MOOCs based on genetic algorithms and TabNet

Salah Eddine Henouda, Fatima Zohra Laallam, Houssam Eddine Aouarib, Mohamed Djouhri
International Journal of Business Intelligence and Data Mining
Online Learning and Analytics
article

GA-TabNet: a novel approach for early dropout prediction in MOOCs based on genetic algorithms and TabNet

Salah Eddine Henouda, Fatima Zohra Laallam, Houssam Eddine Aouarib, Mohamed Djouhri
article en

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

International Journal of Business Intelligence and Data MiningVol. 1(1)
Openalex Percentile: Top 72%
Online Learning and Analytics
DOISourceOpenAlex
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GA-TabNet: a novel approach for early dropout prediction in MOOCs based on genetic algorithms and TabNet — Salah Eddine Henouda, Fatima Zohra Laallam, et al. · International Journal of Business Intelligence and Data Mining (2025) | TGRS Research Map | TGRS