Employing a Biofeedback Method Based on Hemispheric Synchronization in Effective Learning

Kaszuba, Katarzyna; Kostek, Bożena

doi:10.1007/978-3-642-23172-8_20

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“…Across 10 folds of cross-validation, SVM achieved a high accuracy of 93.3% and 87.5% for two datasets using features from four EEG channels, and KNN achieved an accuracy of 87.5% and 86.7% using the same datasets using a single EEG channel. Kaszuba & Kostek (2012) chose One Rule, LADTree, and Logistic Model Tree (LMT) to classify learners' hemispherical synchronization state. The data used was collected from an EEG device while students were performing several tests.…”

Section: Overview Of the Studiesmentioning

confidence: 99%

On the joint use of Artificial Intelligence and Brain-Imaging Techniques in Technology-enhanced Learning Environments: A Systematic Literature Review

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et al. 2021

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Recent meta-analysis and literature reviews support that adaptive learning systems are components of effective instruction. These exciting results are motivating researchers to explore new technologies that provide relevant students' information to promote a better-personalized experience for students to achieve better learning outcomes in technology-enhanced learning environments. A new trend is related to the studies that use brain-imaging techniques to provide relevant students' information for educational systems, aiming to enable an enhanced personalized experience. Some of these studies are making use of artificial intelligence to provide real-time monitoring of students' cognitive phenomena supplied by brain-imaging techniques such as electroencephalography and functional magnetic resonance imaging. Therefore, considering the relevance of the application of artificial intelligence in studies that use brain-imaging techniques combined with technology-enhanced learning environments and the lack of a current understanding of how these techniques have been used in this context, we present a systematic literature review (SLR) that aims to explore which artificial intelligence algorithms have been adopted, what are their purposes in studies that apply brain-imaging techniques in educational technologies and which were the results reported in these studies related to the use of artificial intelligence algorithms. The systematic literature review was conducted according to the recommendation of a well-accepted guideline to perform a rigorous review of the current literature. The search was conducted in seven academic databases in January 2020 and resulted in a total of 6089 studies that was reduced to 20 studies for the final analysis.

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Section: Overview Of the Studiesmentioning

confidence: 99%