{"id":"https://openalex.org/W4400112764","doi":"https://doi.org/10.1145/3674840","title":"A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models","display_name":"A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models","publication_year":2024,"publication_date":"2024-06-28","ids":{"openalex":"https://openalex.org/W4400112764","doi":"https://doi.org/10.1145/3674840"},"language":"en","primary_location":{"id":"doi:10.1145/3674840","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674840","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5079707067","display_name":"H. Zhang","orcid":"https://orcid.org/0009-0000-1991-2163"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hengyuan Zhang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014957271","display_name":"Zitao Liu","orcid":"https://orcid.org/0000-0003-0491-307X"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zitao Liu","raw_affiliation_strings":["Guangdong Institute of Smart Education, Jinan University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Institute of Smart Education, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023899239","display_name":"Chenming Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenming Shang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007540812","display_name":"D. Li","orcid":"https://orcid.org/0009-0003-4139-7841"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawei Li","raw_affiliation_strings":["Halicioglu Data Science Institute, University of California, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"Halicioglu Data Science Institute, University of California, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101626204","display_name":"Yong Jiang","orcid":"https://orcid.org/0000-0002-4260-1395"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Jiang","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079707067"],"corresponding_institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.7801,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91422142,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"19","issue":"2","first_page":"1","last_page":"25"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9939000010490417,"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"}},{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9789999723434448,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.922335147857666},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8560015559196472},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7401026487350464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7162314057350159},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6918095350265503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.607014536857605},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5207414627075195},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5127500295639038},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.46651163697242737},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.45235636830329895},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42918404936790466},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.417305588722229},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.36244016885757446},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33321288228034973}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.922335147857666},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8560015559196472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7401026487350464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7162314057350159},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6918095350265503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.607014536857605},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5207414627075195},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5127500295639038},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.46651163697242737},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.45235636830329895},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42918404936790466},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.417305588722229},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.36244016885757446},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33321288228034973},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3674840","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674840","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6899999976158142,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2369050462","display_name":null,"funder_award_id":"2022YFC3303600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W105592555","https://openalex.org/W123693119","https://openalex.org/W160448112","https://openalex.org/W650350307","https://openalex.org/W1562092080","https://openalex.org/W1597703949","https://openalex.org/W1959691478","https://openalex.org/W2015040676","https://openalex.org/W2064675550","https://openalex.org/W2150884987","https://openalex.org/W2559094423","https://openalex.org/W2603824136","https://openalex.org/W2605961645","https://openalex.org/W2734246064","https://openalex.org/W2788574423","https://openalex.org/W2797581104","https://openalex.org/W2805035427","https://openalex.org/W2890071599","https://openalex.org/W2907913484","https://openalex.org/W2913933519","https://openalex.org/W2916628745","https://openalex.org/W2953577593","https://openalex.org/W2955931418","https://openalex.org/W2966684417","https://openalex.org/W2980472839","https://openalex.org/W2997882704","https://openalex.org/W3035524453","https://openalex.org/W3038147222","https://openalex.org/W3040479400","https://openalex.org/W3043431195","https://openalex.org/W3043869244","https://openalex.org/W3046437295","https://openalex.org/W3046782012","https://openalex.org/W3082341085","https://openalex.org/W3091588028","https://openalex.org/W3092100739","https://openalex.org/W3093783890","https://openalex.org/W3102281445","https://openalex.org/W3113679918","https://openalex.org/W3114202091","https://openalex.org/W3128513560","https://openalex.org/W3154349795","https://openalex.org/W3156636935","https://openalex.org/W3168105984","https://openalex.org/W3171435422","https://openalex.org/W3205662613","https://openalex.org/W3209236561","https://openalex.org/W4224316526","https://openalex.org/W4225753930","https://openalex.org/W4230150613","https://openalex.org/W4282977274","https://openalex.org/W4283452773","https://openalex.org/W4283644089","https://openalex.org/W4287121196","https://openalex.org/W4321012315","https://openalex.org/W4367046760","https://openalex.org/W4382318135","https://openalex.org/W4385567093","https://openalex.org/W4385571413","https://openalex.org/W4404783538","https://openalex.org/W6621483976","https://openalex.org/W6778556382","https://openalex.org/W6796487566"],"related_works":["https://openalex.org/W2797441709","https://openalex.org/W2346578521","https://openalex.org/W4297660007","https://openalex.org/W4377704659","https://openalex.org/W2886918272","https://openalex.org/W4387589990","https://openalex.org/W2943982549","https://openalex.org/W3101055019","https://openalex.org/W2910028250","https://openalex.org/W4241566321"],"abstract_inverted_index":{"Knowledge":[0],"tracing":[1],"(KT)":[2],"plays":[3],"a":[4,124,205,245,262,296,313,389],"crucial":[5,60,197],"role":[6],"in":[7,26,52,102,135,165,204,304,397],"predicting":[8],"students\u2019":[9,62,276],"future":[10],"performance":[11],"by":[12],"analyzing":[13],"their":[14,334],"historical":[15],"learning":[16,41,230,241,317],"processes.":[17],"Deep":[18],"neural":[19],"networks":[20],"(DNNs)":[21],"have":[22,186,411],"shown":[23],"great":[24],"potential":[25],"solving":[27],"the":[28,45,54,69,82,86,105,138,146,152,155,167,192,200,215,218,235,252,282,289,323,331,356,362,371,414],"KT":[29,46,174,269,395],"problem.":[30],"However,":[31,79,234],"there":[32,122],"still":[33],"exist":[34],"some":[35],"important":[36],"challenges":[37],"when":[38],"applying":[39],"deep":[40,172,240,393],"techniques":[42,242],"to":[43,81,137,185,198,224,249,294,321,349],"model":[44,193,405],"process.":[47],"The":[48,161,381],"first":[49],"challenge":[50,163],"lies":[51,164],"modeling":[53],"individual":[55],"question":[56,84,92,106,110,119,157,283,306,336,363],"information.":[57],"This":[58,97,142,211,272],"is":[59,123,196,319],"because":[61],"knowledge":[63,73,111,158,277,301,337,357,366],"acquisition":[64,112,159,278,302,338,358,367],"on":[65,116,355,375,418],"questions":[66,128,328],"that":[67,114,207,385],"share":[68],"same":[70],"set":[71],"of":[72,89,104,127,140,148,154,191,239,291,325,333,392,399],"components":[74],"(KCs)":[75],"may":[76,93,181],"vary":[77],"significantly.":[78],"due":[80],"large":[83],"bank,":[85],"average":[87],"number":[88],"interactions":[90],"per":[91],"not":[94,182],"be":[95,183],"sufficient.":[96],"limitation":[98],"can":[99,143],"potentially":[100],"result":[101],"overfitting":[103,149],"embedding":[107],"and":[108,150,189,221,228,284,299,307,329,364,416],"inaccurate":[109],"state":[113,279,303],"relies":[115],"its":[117],"corresponding":[118,335],"representation.":[120],"Furthermore,":[121],"considerable":[125],"portion":[126],"receiving":[129],"relatively":[130],"less":[131,326],"interaction":[132],"from":[133,170,361],"students":[134],"comparison":[136],"majority":[139],"questions.":[141],"further":[144],"increase":[145],"risk":[147],"lower":[151],"accuracy":[153,332,401],"obtained":[156,360],"state.":[160],"second":[162],"interpreting":[166],"prediction":[168,202,219,254,347,352,400],"results":[169,203,220,353,383],"existing":[171],"learning-based":[173,394],"models.":[175],"In":[176],"real-world":[177,378],"applications,":[178],"while":[179,402],"it":[180,195],"necessary":[184],"complete":[187],"transparency":[188],"interpretability":[190],"parameters,":[194],"present":[199],"model\u2019s":[201,253],"manner":[206],"teachers":[208,213,248],"find":[209],"interpretable.":[210],"makes":[212],"accept":[214],"rationale":[216],"behind":[217],"utilize":[222],"them":[223],"design":[225],"teaching":[226],"activities":[227],"tailored":[229],"strategies":[231],"for":[232,247,268,310],"students.":[233],"inherent":[236],"black-box":[237],"nature":[238],"often":[243],"poses":[244],"hurdle":[246],"fully":[250],"embrace":[251],"results.":[255],"To":[256,407],"address":[257],"these":[258],"challenges,":[259],"we":[260,410],"propose":[261],"Question-centric":[263],"Multi-experts":[264],"Contrastive":[265],"Learning":[266],"framework":[267,273,374],"called":[270],"Q-MCKT.":[271],"explicitly":[274],"models":[275,396],"at":[280,421],"both":[281,305],"concept":[285,308,365],"levels.":[286],"It":[287],"leverages":[288],"mixture":[290],"experts":[292],"technique":[293],"capture":[295],"more":[297],"robust":[298],"accurate":[300],"levels":[309],"prediction.":[311],"Additionally,":[312],"fine-grained":[314],"question-centric":[315],"contrastive":[316],"task":[318],"introduced":[320],"enhance":[322],"representations":[324],"interactive":[327],"improve":[330],"states.":[339],"Moreover,":[340],"Q-MCKT":[341,373],"utilizes":[342],"an":[343],"item":[344],"response":[345],"theory-based":[346],"layer":[348],"generate":[350],"interpretable":[351],"based":[354],"states":[359],"modules.":[368],"We":[369],"evaluate":[370],"proposed":[372],"four":[376],"public":[377],"educational":[379],"datasets.":[380],"experimental":[382],"demonstrate":[384],"our":[386,419],"approach":[387],"outperforms":[388],"wide":[390],"range":[391],"terms":[398],"maintaining":[403],"better":[404],"interpretability.":[406],"ensure":[408],"reproducibility,":[409],"provided":[412],"all":[413],"datasets":[415],"code":[417],"website":[420],"https://github.com/rattlesnakey/Q-MCKT":[422],".":[423]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}