{"id":"https://openalex.org/W4319064557","doi":"https://doi.org/10.1108/dta-05-2022-0199","title":"Multimodal Fast\u2013Slow Neural Network for learning engagement evaluation","display_name":"Multimodal Fast\u2013Slow Neural Network for learning engagement evaluation","publication_year":2023,"publication_date":"2023-02-03","ids":{"openalex":"https://openalex.org/W4319064557","doi":"https://doi.org/10.1108/dta-05-2022-0199"},"language":"en","primary_location":{"id":"doi:10.1108/dta-05-2022-0199","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-05-2022-0199","pdf_url":null,"source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-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/A5030727651","display_name":"Lizhao Zhang","orcid":"https://orcid.org/0000-0002-2510-1575"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lizhao Zhang","raw_affiliation_strings":["National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-2510-1575","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053514094","display_name":"Jui-Long Hung","orcid":"https://orcid.org/0000-0002-7710-7231"},"institutions":[{"id":"https://openalex.org/I120156002","display_name":"Boise State University","ror":"https://ror.org/02e3zdp86","country_code":"US","type":"education","lineage":["https://openalex.org/I120156002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jui-Long Hung","raw_affiliation_strings":["Department of Educational Technology, Boise State University, Boise, Idaho, USA"],"raw_orcid":"https://orcid.org/0000-0002-7710-7231","affiliations":[{"raw_affiliation_string":"Department of Educational Technology, Boise State University, Boise, Idaho, USA","institution_ids":["https://openalex.org/I120156002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011275854","display_name":"Xu Du","orcid":"https://orcid.org/0000-0001-9069-6109"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Du","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9069-6109","affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348547","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-1135-8353"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021392727","display_name":"Zhuang Hu","orcid":"https://orcid.org/0000-0002-7207-5568"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuang Hu","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9859,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.72806159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"57","issue":"3","first_page":"418","last_page":"435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9975000023841858,"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":0.9975000023841858,"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"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9882000088691711,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.82844477891922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7438358068466187},{"id":"https://openalex.org/keywords/asynchrony","display_name":"Asynchrony (computer programming)","score":0.7065017819404602},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.6932028532028198},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5558621287345886},{"id":"https://openalex.org/keywords/originality","display_name":"Originality","score":0.5240143537521362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48277273774147034},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4554831385612488},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.452980637550354},{"id":"https://openalex.org/keywords/observable","display_name":"Observable","score":0.4529206156730652},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4209854304790497},{"id":"https://openalex.org/keywords/qualitative-research","display_name":"Qualitative research","score":0.16352617740631104}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.82844477891922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7438358068466187},{"id":"https://openalex.org/C2779019669","wikidata":"https://www.wikidata.org/wiki/Q25203946","display_name":"Asynchrony (computer programming)","level":3,"score":0.7065017819404602},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.6932028532028198},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5558621287345886},{"id":"https://openalex.org/C2776950860","wikidata":"https://www.wikidata.org/wiki/Q2914681","display_name":"Originality","level":3,"score":0.5240143537521362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48277273774147034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4554831385612488},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.452980637550354},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.4529206156730652},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4209854304790497},{"id":"https://openalex.org/C190248442","wikidata":"https://www.wikidata.org/wiki/Q839486","display_name":"Qualitative research","level":2,"score":0.16352617740631104},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/dta-05-2022-0199","is_oa":false,"landing_page_url":"https://doi.org/10.1108/dta-05-2022-0199","pdf_url":null,"source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W22229905","https://openalex.org/W1491151700","https://openalex.org/W1498436455","https://openalex.org/W1540429825","https://openalex.org/W1548915175","https://openalex.org/W1983412528","https://openalex.org/W1985867508","https://openalex.org/W1994094855","https://openalex.org/W2000933650","https://openalex.org/W2021427605","https://openalex.org/W2026012689","https://openalex.org/W2048688498","https://openalex.org/W2050482434","https://openalex.org/W2051663518","https://openalex.org/W2077395415","https://openalex.org/W2087846093","https://openalex.org/W2109944718","https://openalex.org/W2114909357","https://openalex.org/W2116940784","https://openalex.org/W2141047785","https://openalex.org/W2151096985","https://openalex.org/W2156503193","https://openalex.org/W2162897826","https://openalex.org/W2163922914","https://openalex.org/W2167065977","https://openalex.org/W2169570446","https://openalex.org/W2182151795","https://openalex.org/W2409832138","https://openalex.org/W2577169973","https://openalex.org/W2583212554","https://openalex.org/W2609275912","https://openalex.org/W2612514724","https://openalex.org/W2619383789","https://openalex.org/W2724238895","https://openalex.org/W2726571484","https://openalex.org/W2729369333","https://openalex.org/W2741351499","https://openalex.org/W2767388699","https://openalex.org/W2769095083","https://openalex.org/W2774548175","https://openalex.org/W2779952608","https://openalex.org/W2793759113","https://openalex.org/W2903831537","https://openalex.org/W2909182718","https://openalex.org/W2919890647","https://openalex.org/W2938441647","https://openalex.org/W2944775932","https://openalex.org/W2946480720","https://openalex.org/W2962735936","https://openalex.org/W2982670714","https://openalex.org/W2988553495","https://openalex.org/W2995682556","https://openalex.org/W3008959835","https://openalex.org/W3022736625","https://openalex.org/W3028965967","https://openalex.org/W3038141818","https://openalex.org/W3039470340","https://openalex.org/W3045133046","https://openalex.org/W3046090708","https://openalex.org/W3108028715","https://openalex.org/W3179226074","https://openalex.org/W4285826119"],"related_works":["https://openalex.org/W2593155302","https://openalex.org/W2041415459","https://openalex.org/W2072812638","https://openalex.org/W3126095231","https://openalex.org/W2352855287","https://openalex.org/W2378906650","https://openalex.org/W2944915449","https://openalex.org/W2102266661","https://openalex.org/W2122229220","https://openalex.org/W4297966918"],"abstract_inverted_index":{"Purpose":[0],"Student":[1],"engagement":[2,20,66,97,139],"is":[3],"a":[4],"key":[5],"factor":[6],"that":[7,91],"connects":[8],"with":[9,25,73,84,153,164],"student":[10],"achievement":[11],"and":[12,35,46,70,131],"retention.":[13],"This":[14,124],"paper":[15],"aims":[16],"to":[17,43,64,77,110,134,151],"identify":[18],"individuals'":[19],"automatically":[21],"in":[22,141],"the":[23,59,79,92,100,113,116,120,136,142,148,154],"classroom":[24],"multimodal":[26,127,162],"data":[27,37,52,83,102,128,163],"for":[28,115],"supporting":[29],"educational":[30],"research.":[31],"Design/methodology/approach":[32],"The":[33,105,144],"video":[34],"electroencephalogram":[36],"of":[38,82,119,138,156],"36":[39],"undergraduates":[40],"were":[41],"collected":[42],"represent":[44],"observable":[45,69,130],"internal":[47,71,132],"information.":[48],"Since":[49],"different":[50,54,85,165],"modal":[51],"have":[53],"granularity,":[55],"this":[56],"study":[57,125],"proposed":[58,93,121,145],"Fast\u2013Slow":[60],"Neural":[61],"Network":[62],"(FSNN)":[63],"detect":[65],"through":[67],"both":[68],"information,":[72],"an":[74],"asynchrony":[75],"structure":[76],"preserve":[78],"sequence":[80],"information":[81,159],"granularity.":[86,166],"Findings":[87],"Experimental":[88],"results":[89,106],"show":[90],"algorithm":[94],"can":[95],"recognize":[96],"better":[98,117],"than":[99],"traditional":[101],"fusion":[103],"methods.":[104],"are":[107],"also":[108],"analyzed":[109],"figure":[111],"out":[112],"reasons":[114],"performance":[118],"FSNN.":[122],"Originality/value":[123],"combined":[126],"from":[129],"aspects":[133],"improve":[135],"accuracy":[137],"detection":[140],"classroom.":[143],"FSNN":[146],"used":[147],"asynchronous":[149],"process":[150],"deal":[152],"problem":[155],"remaining":[157],"sequential":[158],"when":[160],"facing":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}