Open-loop neuroadaptive system for enhancing student's cognitive abilities in learning
Neuroeducation seeks to implement knowledge about neural mechanisms of learning into educational practice and to understand the impact of learning itself. The crucial tasks in this field are to evaluate and to enhance cognitive abilities, that are used in monitoring educational performance, but also...
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| Veröffentlicht in: | IEEE access 2024, Vol.12, p.1-1 |
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| creator | Grubov, Vadim V. Khramova, Marina V. Goman, Sergey Badarin, Artem A. Kurkin, Semen A. Andrikov, Denis A. Pitsik, Elena Antipov, Vladimir Petushok, Elena Brusinskii, Nikita Bukina, Tatyana Fedorov, Alexander A. Hramov, Alexander E. |
| description | Neuroeducation seeks to implement knowledge about neural mechanisms of learning into educational practice and to understand the impact of learning itself. The crucial tasks in this field are to evaluate and to enhance cognitive abilities, that are used in monitoring educational performance, but also known to greatly impact learning process. Contemporary neuroscience achieved significant progress in measuring brain cognitive abilities through mental state assessment. Popular approach to this task based on brain-computer interface can be difficult to implement in the context of education, but general concept of neuroadaptation is still plausible. In this study, we propose open-loop neuroadaptive system for enhancing student's cognitive abilities in learning. Assessment of cognitive abilities is based on the concept of executive functions. We design EEG study with special tests and use combined analysis of behavioral and brain activity to assess the level of development of cognitive abilities. Feedback in this system is implemented in the form of recommendations aimed to develop and enhance underdeveloped cognitive abilities and skills. Recommendations have form of various types of extracurricular activities and are based on extensive literature search. This is the system with open-loop adaptation, as it can assess cognitive abilities, provide feedback aimed to enhance these abilities and then after a period of time it can assess cognitive abilities again as a part of the next loop. We believe that developed neuroadaptive system has a potential to be used in educational institutes. |
| doi_str_mv | 10.1109/ACCESS.2024.3383847 |
| format | Article |
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The crucial tasks in this field are to evaluate and to enhance cognitive abilities, that are used in monitoring educational performance, but also known to greatly impact learning process. Contemporary neuroscience achieved significant progress in measuring brain cognitive abilities through mental state assessment. Popular approach to this task based on brain-computer interface can be difficult to implement in the context of education, but general concept of neuroadaptation is still plausible. In this study, we propose open-loop neuroadaptive system for enhancing student's cognitive abilities in learning. Assessment of cognitive abilities is based on the concept of executive functions. We design EEG study with special tests and use combined analysis of behavioral and brain activity to assess the level of development of cognitive abilities. Feedback in this system is implemented in the form of recommendations aimed to develop and enhance underdeveloped cognitive abilities and skills. Recommendations have form of various types of extracurricular activities and are based on extensive literature search. This is the system with open-loop adaptation, as it can assess cognitive abilities, provide feedback aimed to enhance these abilities and then after a period of time it can assess cognitive abilities again as a part of the next loop. We believe that developed neuroadaptive system has a potential to be used in educational institutes.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2024.3383847</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>behavioral characteristics ; Brain models ; cognitive abilities ; Cognitive ability ; decision support system ; Decision support systems ; Education ; educational neuroscience ; electroencephalogram ; Electroencephalography ; executive functions ; Extracurricular activities ; Feedback ; Human-computer interface ; Learning ; Neural engineering ; Neuroadaptive system ; neurophysiological characteristics ; Neuroscience ; Open loop systems ; open-loop ; Performance evaluation ; Physiology ; Recording ; Task analysis ; Visualization</subject><ispartof>IEEE access, 2024, Vol.12, p.1-1</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2747-4eeae3d9c8f9df7163d91da700b24bf81a5762c674ab3b9dd55c3a899da770ab3</cites><orcidid>0000-0002-3438-5717 ; 0000-0002-6392-4580 ; 0000-0003-0359-0897 ; 0009-0003-9612-0305 ; 0000-0003-2491-2592 ; 0000-0003-1850-2394 ; 0000-0002-3212-5890 ; 0000-0003-2787-2530 ; 0000-0003-2658-4545</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10487923$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,4010,27610,27900,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Grubov, Vadim V.</creatorcontrib><creatorcontrib>Khramova, Marina V.</creatorcontrib><creatorcontrib>Goman, Sergey</creatorcontrib><creatorcontrib>Badarin, Artem A.</creatorcontrib><creatorcontrib>Kurkin, Semen A.</creatorcontrib><creatorcontrib>Andrikov, Denis A.</creatorcontrib><creatorcontrib>Pitsik, Elena</creatorcontrib><creatorcontrib>Antipov, Vladimir</creatorcontrib><creatorcontrib>Petushok, Elena</creatorcontrib><creatorcontrib>Brusinskii, Nikita</creatorcontrib><creatorcontrib>Bukina, Tatyana</creatorcontrib><creatorcontrib>Fedorov, Alexander A.</creatorcontrib><creatorcontrib>Hramov, Alexander E.</creatorcontrib><title>Open-loop neuroadaptive system for enhancing student's cognitive abilities in learning</title><title>IEEE access</title><addtitle>Access</addtitle><description>Neuroeducation seeks to implement knowledge about neural mechanisms of learning into educational practice and to understand the impact of learning itself. The crucial tasks in this field are to evaluate and to enhance cognitive abilities, that are used in monitoring educational performance, but also known to greatly impact learning process. Contemporary neuroscience achieved significant progress in measuring brain cognitive abilities through mental state assessment. Popular approach to this task based on brain-computer interface can be difficult to implement in the context of education, but general concept of neuroadaptation is still plausible. In this study, we propose open-loop neuroadaptive system for enhancing student's cognitive abilities in learning. Assessment of cognitive abilities is based on the concept of executive functions. We design EEG study with special tests and use combined analysis of behavioral and brain activity to assess the level of development of cognitive abilities. Feedback in this system is implemented in the form of recommendations aimed to develop and enhance underdeveloped cognitive abilities and skills. Recommendations have form of various types of extracurricular activities and are based on extensive literature search. This is the system with open-loop adaptation, as it can assess cognitive abilities, provide feedback aimed to enhance these abilities and then after a period of time it can assess cognitive abilities again as a part of the next loop. 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The crucial tasks in this field are to evaluate and to enhance cognitive abilities, that are used in monitoring educational performance, but also known to greatly impact learning process. Contemporary neuroscience achieved significant progress in measuring brain cognitive abilities through mental state assessment. Popular approach to this task based on brain-computer interface can be difficult to implement in the context of education, but general concept of neuroadaptation is still plausible. In this study, we propose open-loop neuroadaptive system for enhancing student's cognitive abilities in learning. Assessment of cognitive abilities is based on the concept of executive functions. We design EEG study with special tests and use combined analysis of behavioral and brain activity to assess the level of development of cognitive abilities. Feedback in this system is implemented in the form of recommendations aimed to develop and enhance underdeveloped cognitive abilities and skills. Recommendations have form of various types of extracurricular activities and are based on extensive literature search. This is the system with open-loop adaptation, as it can assess cognitive abilities, provide feedback aimed to enhance these abilities and then after a period of time it can assess cognitive abilities again as a part of the next loop. 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| subjects | behavioral characteristics Brain models cognitive abilities Cognitive ability decision support system Decision support systems Education educational neuroscience electroencephalogram Electroencephalography executive functions Extracurricular activities Feedback Human-computer interface Learning Neural engineering Neuroadaptive system neurophysiological characteristics Neuroscience Open loop systems open-loop Performance evaluation Physiology Recording Task analysis Visualization |
| title | Open-loop neuroadaptive system for enhancing student's cognitive abilities in learning |
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