{"id":"https://openalex.org/W4406416712","doi":"https://doi.org/10.1109/tale62452.2024.10834376","title":"Video-Based Recognition of Online Learning Behaviors Using Attention Mechanisms","display_name":"Video-Based Recognition of Online Learning Behaviors Using Attention Mechanisms","publication_year":2024,"publication_date":"2024-12-09","ids":{"openalex":"https://openalex.org/W4406416712","doi":"https://doi.org/10.1109/tale62452.2024.10834376"},"language":"en","primary_location":{"id":"doi:10.1109/tale62452.2024.10834376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tale62452.2024.10834376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)","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/A5014018483","display_name":"Bingchao Huang","orcid":null},"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":"Bingchao Huang","raw_affiliation_strings":["Beihang University,Sino-French Engineer School,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,Sino-French Engineer School,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":["Beihang University,Sino-French Engineer School,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,Sino-French Engineer School,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406973","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0002-3262-653X"},"institutions":[{"id":"https://openalex.org/I1902872","display_name":"EURECOM","ror":"https://ror.org/00sse7z02","country_code":"FR","type":"education","lineage":["https://openalex.org/I1902872","https://openalex.org/I205703379"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["EURECOM Sorbonne University,Biot,France"],"affiliations":[{"raw_affiliation_string":"EURECOM Sorbonne University,Biot,France","institution_ids":["https://openalex.org/I1902872","https://openalex.org/I39804081"]}]},{"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"],"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/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":["Central University of Finance and Economics,School of Information,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Central University of Finance and Economics,School of Information,Beijing,China","institution_ids":["https://openalex.org/I137867983"]}]},{"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":["Beihang University,School of Computer Science and Engineering,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,School of Computer Science and Engineering,Beijing,China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5014018483"],"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":0.25284479,"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":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9851999878883362,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9358999729156494,"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/computer-science","display_name":"Computer science","score":0.7697471976280212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4885431230068207},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.33087122440338135}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7697471976280212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4885431230068207},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.33087122440338135}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tale62452.2024.10834376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tale62452.2024.10834376","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)","raw_type":"proceedings-article"},{"id":"pmh:oai:fr.eurecom:8034","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196942","display_name":"Graduate School and Research Center in Digital Science (EURECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1902872","host_organization_name":"EURECOM","host_organization_lineage":["https://openalex.org/I1902872"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"TALE 2024, IEEE International Conference on Teaching, Assessment and Learning for Engineering, 9-12 December 2024, Bengaluru, India","raw_type":"Conference"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2962949934","https://openalex.org/W2982083293","https://openalex.org/W3128826581","https://openalex.org/W3138516171","https://openalex.org/W3146830617","https://openalex.org/W3154593767","https://openalex.org/W3191120830","https://openalex.org/W3194629912","https://openalex.org/W3202672969","https://openalex.org/W4206336798","https://openalex.org/W4246399668","https://openalex.org/W4288327876","https://openalex.org/W4312986923","https://openalex.org/W4386071839","https://openalex.org/W4387225729","https://openalex.org/W6764045775","https://openalex.org/W6856857450","https://openalex.org/W7039869051"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,199],"the":[1,95,118,123,127,131,150,172,180,204],"field":[2],"of":[3,36,57,60,103,112,122,130,149,166,184,192,196,207],"education,":[4],"identifying":[5,77],"students\u2019":[6,17,61,197],"online":[7,79],"learning":[8,18,80],"behavior":[9],"is":[10,85,212],"a":[11,46,53,68,100,110,137,155],"very":[12],"effective":[13],"means":[14],"to":[15,115,144,160,178],"understand":[16],"status":[19],"and":[20,65,90,107,125,164,182],"improve":[21],"teaching":[22],"efficiency.":[23],"However,":[24],"previous":[25],"research":[26],"has":[27,154],"mostly":[28],"been":[29],"based":[30,72],"on":[31,73],"older":[32],"models.":[33],"The":[34,83,152,168],"shortage":[35],"datasets":[37],"in":[38,216],"this":[39,49,185],"task":[40],"can":[41],"also":[42,170,213],"be":[43,214],"regarded":[44],"as":[45,105,176],"problem.":[47],"Therefore,":[48],"study":[50,169],"first":[51,108],"constructed":[52],"video":[54],"dataset":[55,175],"consisting":[56],"10":[58],"types":[59],"online-learning":[62],"behaviors":[63,81],"(SOLB),":[64],"then":[66],"proposed":[67,186],"Neural":[69,92],"Network":[70],"model":[71],"Attention":[74],"mechanism":[75,140],"for":[76,194],"student":[78],"(CNN-Swin).":[82],"network":[84,153],"inspired":[86],"by":[87],"Swin":[88],"Transformer":[89],"Convolutional":[91],"Network(CNN)":[93],"at":[94],"same":[96],"time.":[97],"It":[98],"takes":[99],"single":[101],"frame":[102],"image":[104,124],"input,":[106],"uses":[109,136],"series":[111],"convolutional":[113],"layers":[114],"efficiently":[116],"extract":[117,145],"primary":[119],"spatial":[120,128,147],"features":[121,148],"reduce":[126],"size":[129],"feature":[132],"map.":[133],"Then,":[134],"it":[135],"local":[138],"Self-Attention":[139],"with":[141,201,209],"window":[142],"translation":[143],"deep":[146],"image.":[151],"high":[156],"prediction":[157],"speed":[158],"due":[159],"its":[161],"low":[162],"complexity":[163],"compression":[165],"inputs.":[167],"adds":[171],"popular":[173],"ImageNet":[174],"pre-training":[177],"demonstrate":[179],"effectiveness":[181],"out-performing":[183],"model,":[187],"which":[188],"finally":[189],"approach":[190],"accuracy":[191],"90.42%":[193],"classification":[195],"behavior.":[198],"comparison":[200],"SOTA":[202],"models,":[203],"outstanding":[205],"perform":[206],"CNN-Swin":[208],"pre-trained":[210],"methods":[211],"proved":[215],"many":[217],"benchmarks.":[218]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}