Decoding student cognitive abilities: a comparative study of explainable AI algorithms in educational data mining

Exploring students’ cognitive abilities has long been an important topic in education. This study employs data-driven artificial intelligence (AI) models supported by explainability algorithms and PSM causal inference to investigate the factors influencing students’ cognitive abilities, and it delve...

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Bibliographic Details
Published in:	Scientific reports Vol. 15; no. 1; pp. 26862 - 20
Main Authors:	Niu, Tianyue, Liu, Ting, Luo, Yiming Taclis, Pang, Patrick Cheong-Iao, Huang, Shuaishuai, Xiang, Ao
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 24.07.2025 Nature Publishing Group Nature Portfolio
Subjects:	631/477 631/477/2811 639/705/117 Accuracy Algorithms Artificial Intelligence Cognition Cognition & reasoning Cognitive abilities Cognitive ability Cognitive development Comparative studies Critical thinking Data mining Data Mining - methods Education Educational data mining Explainability algorithms Female Humanities and Social Sciences Humans Hypotheses Machine learning Male multidisciplinary Research methodology Science Science (multidisciplinary) Skills Socioeconomic factors Socioeconomic status Statistical methods Student teacher relationship Students Students - psychology Educational data mining Explainability algorithms Students Machine learning Cognitive abilities
ISSN:	2045-2322, 2045-2322
Online Access:	Get full text
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