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





Brain-imaging Techniques, Technology-enhanced Learning Environments, Artificial Intelligence Algorithms


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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Biografia do Autor

Kamilla Tenório, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Jário Santos, University of São Paulo

ICMC, University of São Paulo, São Carlos

Victor Accete, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Sterfanno Remigio, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Alan Pedro da Silva, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Diego Dermeval, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Ig Ibert Bittencourt, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas

Leonardo Brandão Marques, Federal University of Alagoas

Center of Excellence for Social Technologies - Computing Institute, Federal University of Alagoas


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TENÓRIO, K.; SANTOS, J.; ACCETE, V.; REMIGIO, S.; DA SILVA, A. P.; DERMEVAL, D.; BITTENCOURT, I. I.; MARQUES, L. B. On the joint use of Artificial Intelligence and Brain-Imaging Techniques in Technology-enhanced Learning Environments: A Systematic Literature Review. Revista Brasileira de Informática na Educação, [S. l.], v. 29, p. 502–518, 2021. DOI: 10.5753/rbie.2021.29.0.502. Disponível em: https://sol.sbc.org.br/journals/index.php/rbie/article/view/2977. Acesso em: 4 dez. 2023.




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