Effects of the binaural wave as a stimulus for student hyperattention: brain frequency records without interactive media context

Bos, Andreia Solange; Donato, Lucília Gomes; Vettori, Marcelo; Zaro, Milton Antônio

doi:10.22161/ijaers.79.24

IJAERS

2020

DOI: 10.22161/ijaers.79.24

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Effects of the binaural wave as a stimulus for student hyperattention: brain frequency records without interactive media context

Andreia Solange Bos¹,

Lucília Gomes Donato²,

Marcelo Vettori³

et al.

Abstract: The brain works with electrochemical, generating brain waves that represent brain activity. The basic frequencies of brain functioning are gamma . With these references it is possible to condition the electrical activity, inducing a specific wave pattern. The way for this to happen is through binaural waves to synchronize brain patterns. This technique is addressed in this study, in the context of interactive media and in the student's attention stimuli, so the sounds are received independently in each ear cre… Show more

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Cited by 2 publications

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EEG in Education: A Scoping Review of Hardware, Software, and Methodological Aspects

Orovas,

Sapounidis,

Volioti

et al. 2024

Sensors

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Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field. Being a multidisciplinary field, neuroeducation requires expertise in various fields such as education, neuroinformatics, psychology, cognitive science, and neuroscience. The need for a comprehensive guide where various important issues are presented and examples of their application in neuroeducation research projects are given is apparent. This paper presents an overview of the current hardware and software options, discusses methodological issues, and gives examples of best practices as found in the recent literature. These were selected by applying the PRISMA statement to results returned by searching PubMed, Scopus, and Google Scholar with the keywords “EEG and neuroeducation” for projects published in the last six years (2018–2024). Apart from the basic background knowledge, two research questions regarding methodological aspects (experimental settings and hardware and software used) and the subject of the research and type of information used from the EEG signals are addressed and discussed.

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EEG in Education: A Scoping Review of Hardware, Software, and Methodological Aspects

Orovas,

Sapounidis,

Volioti

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

Empirical Evidence during the Implementation of an Educational Chatbot with the Electroencephalogram Metric

Bos¹,

Pizzato²,

Vettori³

et al. 2020

Self Cite

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A student's attention status during a digital conversation can differ when talking to an intelligent agent, that is, a chatterbot interactive. There is evidence that brain waves have different oscillations during the study. A virtual platform with an artificial intelligence chatterbot was explored in this study. During the study, participants were asked to use the Neurosky Mindwave sensor to assess their attention levels in real time. Statistical analyses of the results revealed significant effects on the participants' attention levels. The chatbot was associated with dominant proportions of delta and theta brain waves in didactic content. Conversation via social interaction chatbot triggered dominant gamma brain waves.

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Effects of the binaural wave as a stimulus for student hyperattention: brain frequency records without interactive media context

Cited by 2 publications

References 5 publications

EEG in Education: A Scoping Review of Hardware, Software, and Methodological Aspects

EEG in Education: A Scoping Review of Hardware, Software, and Methodological Aspects

Empirical Evidence during the Implementation of an Educational Chatbot with the Electroencephalogram Metric

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