{"id":"https://openalex.org/W4408077831","doi":"https://doi.org/10.1007/s44163-025-00240-w","title":"Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure","display_name":"Prediction of teaching quality in the context of smart education: application of multimodal data fusion and complex network topology structure","publication_year":2025,"publication_date":"2025-03-01","ids":{"openalex":"https://openalex.org/W4408077831","doi":"https://doi.org/10.1007/s44163-025-00240-w"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00240-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00240-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00240-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00240-w.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009144836","display_name":"Chunzhong Li","orcid":"https://orcid.org/0000-0001-7897-5850"},"institutions":[{"id":"https://openalex.org/I188935350","display_name":"Anhui University of Finance and Economics","ror":"https://ror.org/0152zzg30","country_code":"CN","type":"education","lineage":["https://openalex.org/I188935350"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chunzhong Li","raw_affiliation_strings":["Institute of Tatiscs and Applied Mathematics, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Institute of Tatiscs and Applied Mathematics, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China","institution_ids":["https://openalex.org/I188935350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072479833","display_name":"Chenglan Liu","orcid":"https://orcid.org/0000-0002-9067-2630"},"institutions":[{"id":"https://openalex.org/I188935350","display_name":"Anhui University of Finance and Economics","ror":"https://ror.org/0152zzg30","country_code":"CN","type":"education","lineage":["https://openalex.org/I188935350"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglan Liu","raw_affiliation_strings":["School of Literature, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Literature, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China","institution_ids":["https://openalex.org/I188935350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113313255","display_name":"Wenliang Ju","orcid":"https://orcid.org/0000-0002-9394-8380"},"institutions":[{"id":"https://openalex.org/I188935350","display_name":"Anhui University of Finance and Economics","ror":"https://ror.org/0152zzg30","country_code":"CN","type":"education","lineage":["https://openalex.org/I188935350"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenliang Ju","raw_affiliation_strings":["Institute of Tatiscs and Applied Mathematics, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Institute of Tatiscs and Applied Mathematics, Anhui University of Finance & Economics, Bengbu, 233030, Anhui, China","institution_ids":["https://openalex.org/I188935350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101283101","display_name":"Yuanquan Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanquan Zhong","raw_affiliation_strings":["Academic Affairs Office, Anhui Wenda University of Information Engineering, Hefei, 231200, Anhui, China"],"affiliations":[{"raw_affiliation_string":"Academic Affairs Office, Anhui Wenda University of Information Engineering, Hefei, 231200, Anhui, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100448724","display_name":"Yonghui Li","orcid":"https://orcid.org/0000-0001-7702-1123"},"institutions":[{"id":"https://openalex.org/I4210156464","display_name":"Anhui Xinhua University","ror":"https://ror.org/053d7x641","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156464"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonghui Li","raw_affiliation_strings":["School of Art, Anhui Xinhua University, Hefei, 231200, Anhui, China"],"affiliations":[{"raw_affiliation_string":"School of Art, Anhui Xinhua University, Hefei, 231200, Anhui, China","institution_ids":["https://openalex.org/I4210156464"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009144836"],"corresponding_institution_ids":["https://openalex.org/I188935350"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":24.1105,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.99243092,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9492999911308289,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13676","display_name":"Educational and Technological Research","score":0.9045000076293945,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12260","display_name":"Educational Technology and Pedagogy","score":0.9039000272750854,"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":0.596331000328064},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5637443661689758},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.5411067008972168},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5222581028938293},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.49244579672813416},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.41211605072021484},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40780800580978394},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33873626589775085},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3381578326225281},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16532433032989502},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10436761379241943},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06836742162704468},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06727635860443115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.596331000328064},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5637443661689758},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.5411067008972168},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5222581028938293},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.49244579672813416},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.41211605072021484},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40780800580978394},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33873626589775085},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3381578326225281},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16532433032989502},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10436761379241943},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06836742162704468},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06727635860443115},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00240-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00240-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00240-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6e0b3668801b4c1e8288d8328b636454","is_oa":true,"landing_page_url":"https://doaj.org/article/6e0b3668801b4c1e8288d8328b636454","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-21 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00240-w","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00240-w","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00240-w.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4408077831.pdf"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W2915621437","https://openalex.org/W3003999301","https://openalex.org/W3006537562","https://openalex.org/W3014018380","https://openalex.org/W3029588370","https://openalex.org/W3035622304","https://openalex.org/W3082665562","https://openalex.org/W3087128966","https://openalex.org/W3110511009","https://openalex.org/W3212386989","https://openalex.org/W3216302037","https://openalex.org/W4210713738","https://openalex.org/W4214713882","https://openalex.org/W4220991771","https://openalex.org/W4224998877","https://openalex.org/W4293824843","https://openalex.org/W4306906954","https://openalex.org/W4318822211","https://openalex.org/W4362581794","https://openalex.org/W4378904127","https://openalex.org/W4379881562","https://openalex.org/W4388879985","https://openalex.org/W4391127843","https://openalex.org/W4401499897"],"related_works":["https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2967030268","https://openalex.org/W2961085424","https://openalex.org/W2185253430","https://openalex.org/W4210345652","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"The":[0,221,264],"existing":[1],"teaching":[2,45,72,215,219,271,293],"quality":[3,73,272],"prediction":[4,39,190,222,273,291],"methods":[5],"only":[6],"rely":[7],"on":[8,225],"single":[9],"modal":[10],"data":[11,197],"such":[12,198],"as":[13,149,199],"students\u2019":[14],"scores,":[15],"and":[16,36,53,63,69,83,100,109,128,146,158,184,203,217,283,289],"do":[17],"not":[18],"fully":[19],"mine":[20],"the":[21,26,38,67,76,92,125,136,140,152,189,194,239,242,248,252,257,281],"complex":[22,50,55,160],"network":[23,47,51,56,126,150,161,231,270],"structure":[24,163],"of":[25,32,71,103,139,236,285,292],"classroom,":[27],"resulting":[28],"in":[29,121,188,238,276],"insufficient":[30],"understanding":[31],"multidimensional":[33],"interaction":[34,61],"relationships":[35],"affecting":[37],"accuracy.":[40],"This":[41],"article":[42,77,278],"constructed":[43],"a":[44,79,159],"interactive":[46],"by":[48],"applying":[49],"theory,":[52],"used":[54,170],"analysis":[57],"to":[58,86,123,134,171,178],"reveal":[59],"classroom":[60,201],"rules":[62],"key":[64,186],"factors,":[65],"improving":[66],"accuracy":[68,235,282],"robustness":[70],"prediction.":[74],"Firstly,":[75],"utilized":[78],"score":[80,245],"management":[81],"system":[82],"intelligent":[84],"cameras":[85],"collect":[87],"multimodal":[88,173,196],"learning":[89,147],"data;":[90],"then,":[91,166],"original":[93],"signal":[94],"was":[95,132,164,169,207,246,255,262],"decomposed":[96],"into":[97],"detail":[98,111],"layers":[99,102,112],"approximation":[101],"different":[104,176],"frequencies":[105],"using":[106,143],"wavelet":[107],"transform,":[108],"high-frequency":[110],"were":[113,156],"processed":[114],"for":[115],"denoising":[116],"through":[117],"threshold":[118],"functions;":[119],"afterwards,":[120],"order":[122],"reduce":[124],"size":[127],"parameters,":[129],"attention":[130,167,226,265],"mechanism":[131,168,227,266],"applied":[133],"screen":[135],"input":[137],"features":[138],"neural":[141,230,269],"network;":[142],"students,":[144],"teachers,":[145],"resources":[148],"nodes,":[151],"connections":[153],"between":[154],"nodes":[155],"analyzed":[157],"topology":[162],"constructed;":[165],"fuse":[172],"data,":[174],"assigning":[175],"weights":[177],"each":[179],"modality,":[180],"integrating":[181],"educational":[182],"information,":[183],"highlighting":[185],"information":[187],"task.":[191],"Through":[192],"testing":[193],"collected":[195],"grades,":[200],"behavior,":[202],"psychological":[204],"characteristics,":[205],"it":[206],"found":[208],"that":[209],"this":[210,277],"article\u2019s":[211],"method":[212],"could":[213],"optimize":[214],"strategies":[216],"improve":[218],"effectiveness.":[220],"model":[223,274],"based":[224],"optimized":[228,267],"deep":[229,268],"achieved":[232],"an":[233],"average":[234,243,258],"94.16%":[237],"first":[240],"test;":[241],"F1":[244],"90.60%;":[247],"AUC":[249],"(Area":[250],"Under":[251],"Curve)":[253],"value":[254],"0.975;":[256],"mean":[259],"square":[260],"error":[261],"0.271.":[263],"studied":[275],"has":[279],"improved":[280],"reliability":[284],"prediction,":[286],"achieving":[287],"comprehensive":[288],"accurate":[290],"quality.":[294]},"counts_by_year":[{"year":2025,"cited_by_count":7}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
