{"id":"https://openalex.org/W4407949502","doi":"https://doi.org/10.1109/fie61694.2024.10893168","title":"An RSB-GNN-Based EEG Approach for Exploring Students' Affective States in E-Learning","display_name":"An RSB-GNN-Based EEG Approach for Exploring Students' Affective States in E-Learning","publication_year":2024,"publication_date":"2024-10-13","ids":{"openalex":"https://openalex.org/W4407949502","doi":"https://doi.org/10.1109/fie61694.2024.10893168"},"language":"en","primary_location":{"id":"doi:10.1109/fie61694.2024.10893168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fie61694.2024.10893168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Frontiers in Education Conference (FIE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100416893","display_name":"Ting Li","orcid":"https://orcid.org/0000-0002-9593-7650"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ting Li","raw_affiliation_strings":["Sino-French Engineer School, Beihang University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sino-French Engineer School, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079167910","display_name":"Chuantao Yin","orcid":"https://orcid.org/0000-0002-0742-0804"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuantao Yin","raw_affiliation_strings":["Sino-French Engineer School, Beihang University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sino-French Engineer School, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102045375","display_name":"Yanmei Chai","orcid":null},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmei Chai","raw_affiliation_strings":["School of Information, Central University of Finance and Economics,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information, Central University of Finance and Economics,Beijing,China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334208","display_name":"Hui Chen","orcid":"https://orcid.org/0000-0003-0277-0597"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Chen","raw_affiliation_strings":["Beihang University,Department of Planning and Finance,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,Department of Planning and Finance,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055420596","display_name":"Wenge Rong","orcid":"https://orcid.org/0000-0002-4229-7215"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenge Rong","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100627876","display_name":"Yuanxin Ouyang","orcid":"https://orcid.org/0000-0002-8687-9129"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanxin Ouyang","raw_affiliation_strings":["School of Computer Science and Engineering, Beihang University,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Beihang University,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100416893"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26835646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8665000200271606,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8665000200271606,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6826431751251221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6406819224357605},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4069634974002838},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2950085401535034},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07524266839027405}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6826431751251221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406819224357605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4069634974002838},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2950085401535034},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07524266839027405}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fie61694.2024.10893168","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fie61694.2024.10893168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Frontiers in Education Conference (FIE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W26396891","https://openalex.org/W1947251450","https://openalex.org/W2002055708","https://openalex.org/W2052097980","https://openalex.org/W2058064543","https://openalex.org/W2072035149","https://openalex.org/W2171618137","https://openalex.org/W2547146855","https://openalex.org/W2599124244","https://openalex.org/W2625929003","https://openalex.org/W2731964405","https://openalex.org/W2768531844","https://openalex.org/W2786768213","https://openalex.org/W2790404832","https://openalex.org/W2792325177","https://openalex.org/W2805929000","https://openalex.org/W2807738726","https://openalex.org/W2899573127","https://openalex.org/W2933627812","https://openalex.org/W2947406682","https://openalex.org/W2950162539","https://openalex.org/W2962905870","https://openalex.org/W2969540327","https://openalex.org/W2977117446","https://openalex.org/W3020169412","https://openalex.org/W3024961463","https://openalex.org/W3089752722","https://openalex.org/W3115745466","https://openalex.org/W3138600019","https://openalex.org/W3159301005","https://openalex.org/W3175508462","https://openalex.org/W3194802919","https://openalex.org/W3207465637","https://openalex.org/W4210820433","https://openalex.org/W4210878028","https://openalex.org/W4285282157","https://openalex.org/W4293660431","https://openalex.org/W4294975166","https://openalex.org/W4312096888","https://openalex.org/W4320000009","https://openalex.org/W4321192254","https://openalex.org/W4321442004","https://openalex.org/W4322622387","https://openalex.org/W4327703846","https://openalex.org/W4380355331","https://openalex.org/W4387431468","https://openalex.org/W4389040783","https://openalex.org/W4402722012"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2390279801","https://openalex.org/W2130428257","https://openalex.org/W4391913857","https://openalex.org/W4308951944","https://openalex.org/W2358668433"],"abstract_inverted_index":{"This":[0],"research":[1,118,203],"paper":[2],"describes":[3],"an":[4],"original":[5],"method":[6],"of":[7,61,94,154,160,191,208,221,268],"affective":[8,48,124,234],"state":[9,125],"recognition":[10,80],"in":[11,20],"the":[12,58,62,89,100,121,137,143,146,152,158,167,184,189,192,206,218,248,262,266,269],"e-learning":[13],"field.":[14],"Emotion":[15],"plays":[16],"a":[17,103,129],"key":[18],"role":[19],"both":[21],"knowledge-building":[22],"and":[23,30,47,64,68,97,156,226,265,275],"mental":[24,245],"health.":[25,246],"In":[26,116],"recent":[27],"years,":[28],"more":[29,31],"emotion":[32,79,227],"researchers":[33],"have":[34],"broken":[35],"through":[36,102,217],"traditional":[37],"questionnaires":[38],"to":[39,43,87,135,150,174,197,211,231,236,260,272],"utilize":[40],"physiological":[41,59],"data":[42],"monitor":[44],"students'":[45,232,273],"cognitive":[46],"states.":[49],"Among":[50],"these":[51],"methods,":[52],"electroencephalography":[53],"(EEG)":[54],"can":[55,256],"directly":[56],"reflect":[57],"activities":[60],"brain":[63,113,172],"has":[65],"unique":[66],"potentials":[67],"advantages":[69],"over":[70],"others.":[71],"For":[72],"analyzing":[73],"this":[74,117,209],"multi-channel":[75],"noised":[76],"signal,":[77],"current":[78,198],"methods":[81,86],"mainly":[82],"use":[83,205,257],"deep":[84,199],"learning":[85,200,215,222,224,240,263],"learn":[88],"spatial":[90],"or":[91,252],"temporal":[92],"representation":[93],"each":[95],"channel,":[96],"then":[98],"process":[99],"classification":[101],"multimodal":[104],"fusion":[105],"strategy,":[106],"while":[107],"emotional":[108,258],"expression":[109],"highly":[110],"relies":[111],"on":[112,183],"functional":[114],"connectivity.":[115],"work,":[119],"for":[120,163],"EEG-based":[122],"learning-centered":[123,233],"recognition,":[126],"we":[127],"adopted":[128],"novel":[130],"residual":[131],"shrinkage":[132],"block":[133],"(RSB)":[134],"construct":[136],"graph":[138],"neural":[139],"network":[140],"(GNN).":[141],"During":[142],"feature":[144],"extraction,":[145],"RSB":[147],"is":[148,195],"designed":[149],"obtain":[151],"features":[153],"interest":[155],"reduce":[157],"influence":[159],"artifact":[161],"noises":[162],"recognition.":[164],"GNN":[165],"considers":[166],"biological":[168],"topology":[169],"among":[170,177],"different":[171,178],"regions":[173],"capture":[175],"relations":[176],"EEG":[179],"channels.":[180],"Extensive":[181],"experiments":[182],"CAL":[185],"dataset":[186],"prove":[187],"that":[188],"performance":[190,241],"proposed":[193],"model":[194],"superior":[196],"methods.":[201],"Prior":[202],"may":[204],"findings":[207],"study":[210],"empower":[212],"adaptive":[213],"self-regulated":[214],"environments":[216],"automated":[219],"recommendation":[220],"strategies,":[223],"contents,":[225],"regulation":[228],"strategies":[229],"according":[230,271],"states,":[235],"further":[237],"improve":[238],"their":[239],"as":[242,244],"well":[243],"On":[247],"other":[249],"hand,":[250],"teachers":[251],"online":[253],"course":[254],"designers":[255],"feedback":[259],"adjust":[261],"materials":[264],"pace":[267],"instruction":[270],"needs":[274],"preferences.":[276]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}