Investigating Cross-Subject Generalization and Personalized Modeling in EEG-Based Cognitive Understanding Prediction for Intelligent Learning Systems

Citation

Shannaq, Boumedyen and Ali, Oualid and AlMaqbali, Said (2026) Investigating Cross-Subject Generalization and Personalized Modeling in EEG-Based Cognitive Understanding Prediction for Intelligent Learning Systems. In: 2026 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2026, 6 May 2026 - 7 May 2026, Manama.

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Abstract

Cognitive analytics using electroencephalography (EEG) can have a lot of potential in terms of intelligent learning systems, but assessment methods tend to ignore the fact that one subject may leak information to another, and thus, overestimate performance. This work explores the cognitive prediction of cognitive understanding through EEG approaches based on 68,831 samples that were recorded on eight subjects and eleven educational videos. It compared five baseline classifiers, which included Logistic Regression, Random Forest, Support Vector Machine, XGBoost, and LightGBM, on three validation strategies and they were on random row split, cross-subject GroupKFold and within-subject stratified modeling validation strategies. Near perfect results were obtained with random row splitting (LightGBM ROC-AUC = 1.0000), which is leakagebased upper-bound performance. Performance was much lower under subject-disjoint validation (optimal ROC-AUC = 0.6628 ± 0.1176 by XGBoost), demonstrating a poor cross-subject extrapolation. Conversely, within-subject modeling had close to perfect discrimination (ROC-AUC 0.999-1.000) among eligible subjects. The discussed leakage-conscious assessment system measures the generalization disjunctions and proves that custom modeling offers a more effective deployment planning. This work provides a methodological validation procedure of neuro-educational information systems and provides a practical implementation advice of EEG-based adaptive learning systems.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: EEG-based learning analytics, Cognitive understanding prediction
Subjects: L Education > LB Theory and practice of education > LB1060 Learning
Divisions: Others
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 04 Aug 2026 06:42
Last Modified: 04 Aug 2026 06:42
URII: http://shdl.mmu.edu.my/id/eprint/16494

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