A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns

A Machine Learning Framework for Classroom EEG Recording Classification: Unveiling Learning-Style Patterns

Classroom EEG recordings classification has the capacity to significantly enhance comprehension and learning by revealing complex neural patterns linked to various cognitive processes. Electroencephalography (EEG) in academic settings allows researchers to study brain activity while students are in...

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Bibliographic Details
Main Authors: Rajamanickam Yuvaraj, Shivam Chadha, A. Amalin Prince, M. Murugappan, Md. Sakib Bin Islam, Md. Shaheenur Islam Sumon, Muhammad E. H. Chowdhury
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Algorithms
Subjects:
classroom EEG
academic
learning style
cross-validation
statistical measurements
automation
Online Access:https://www.mdpi.com/1999-4893/17/11/503
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