Relations of attention and meditation level with learning in engineering education

Basit Öğe Kaydı
dc.authorid57201072412
dc.authorid35086864100
dc.authorid57207630420
dc.authorid55488573000
dc.contributor.authorÜlker B.
dc.contributor.authorTabakcio?lu M.B.
dc.contributor.authorÇizmeci H.
dc.contributor.authorAyberkin D.
dc.date.accessioned20.04.201910:49:12
dc.date.accessioned2019-04-20T21:43:12Z
dc.date.available20.04.201910:49:12
dc.date.available2019-04-20T21:43:12Z
dc.date.issued2017
dc.departmentBayburt Üniversitesien_US
dc.description9th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2017
dc.description.abstractNeurons use electricity in order to communicate to each other. Due to numerous signals sent by neurons, there are oodles of electrical activity in the brain. Sensitive equipment like electroencephalogram (EEG) biosensor perceives the brainwaves emanated from neurons. Beta waves are responsible for problem solving or decision making and associated with attention. Alpha waves are associated with now and meditation. Neurosky EEG biosensor perceives the brainwaves and transforms these brainwaves into attention and meditation values. In this study, Neurosky EEG biosensor is used for measuring the attention and meditation levels of students. A program is developed in C# medium. The developed program records raw brainwave data, attention and meditation average while the students are studying. As the attention and meditation levels are high, the students learn the subjects in the course. If predetermined meditation and attention level are not caught, the developed program does not give permission to pass to another subject. Because of that the students have less meditation and attention average than the predetermined value; they get fewer grades in the exam. © 2017 IEEE.en_US
dc.identifier.doi10.1109/ECAI.2017.8166407
dc.identifier.endpage4
dc.identifier.isbn9.78151E+12
dc.identifier.scopus2-s2.0-85043338253en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1
dc.identifier.urihttps://dx.doi.org/10.1109/ECAI.2017.8166407
dc.identifier.urihttps://hdl.handle.net/20.500.12403/451
dc.identifier.volume2017-January
dc.identifier.wosWOS:000425865900023en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofProceedings of the 9th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2017en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBrain computer interface (BCI)
dc.subjectBrainwaves
dc.subjectEducation
dc.subjectEEG
dc.subjectEEG biosensor
dc.subjectNeurosky
dc.subjectArtificial intelligence
dc.subjectBiosensors
dc.subjectBrain
dc.subjectBrain computer interface
dc.subjectDecision making
dc.subjectEducation
dc.subjectElectroencephalography
dc.subjectInterfaces (computer)
dc.subjectNeurons
dc.subjectProblem solving
dc.subjectAlpha waves
dc.subjectAttention level
dc.subjectBrain wave
dc.subjectElectrical activities
dc.subjectElectro-encephalogram (EEG)
dc.subjectLearning in engineering
dc.subjectNeurosky
dc.subjectSensitive equipment
dc.subjectStudents
dc.subjectBrain computer interface (BCI)
dc.subjectBrainwaves
dc.subjectEducation
dc.subjectEEG
dc.subjectEEG biosensor
dc.subjectNeurosky
dc.subjectArtificial intelligence
dc.subjectBiosensors
dc.subjectBrain
dc.subjectBrain computer interface
dc.subjectDecision making
dc.subjectEducation
dc.subjectElectroencephalography
dc.subjectInterfaces (computer)
dc.subjectNeurons
dc.subjectProblem solving
dc.subjectAlpha waves
dc.subjectAttention level
dc.subjectBrain wave
dc.subjectElectrical activities
dc.subjectElectro-encephalogram (EEG)
dc.subjectLearning in engineering
dc.subjectNeurosky
dc.subjectSensitive equipment
dc.subjectStudents
dc.titleRelations of attention and meditation level with learning in engineering educationen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu