{"id":"https://openalex.org/W3176719537","doi":"https://doi.org/10.1145/3450613.3456831","title":"Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor Factorization","display_name":"Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor Factorization","publication_year":2021,"publication_date":"2021-06-21","ids":{"openalex":"https://openalex.org/W3176719537","doi":"https://doi.org/10.1145/3450613.3456831","mag":"3176719537"},"language":"en","primary_location":{"id":"doi:10.1145/3450613.3456831","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3450613.3456831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization","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/A5069388694","display_name":"Chunpai Wang","orcid":"https://orcid.org/0000-0003-3162-4310"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunpai Wang","raw_affiliation_strings":["University at Albany - SUNY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany - SUNY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110781770","display_name":"Shaghayegh Sahebi","orcid":null},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shaghayegh Sahebi","raw_affiliation_strings":["University at Albany - SUNY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany - SUNY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066502752","display_name":"Siqian Zhao","orcid":"https://orcid.org/0009-0008-3913-7836"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siqian Zhao","raw_affiliation_strings":["University at Albany - SUNY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University at Albany - SUNY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037674585","display_name":"Peter Brusilovsky","orcid":"https://orcid.org/0000-0002-1902-1464"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Brusilovsky","raw_affiliation_strings":["University of Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015301698","display_name":"Laura O. Moraes","orcid":"https://orcid.org/0000-0003-0965-6703"},"institutions":[{"id":"https://openalex.org/I122140584","display_name":"Universidade Federal do Rio de Janeiro","ror":"https://ror.org/03490as77","country_code":"BR","type":"education","lineage":["https://openalex.org/I122140584"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Laura O. Moraes","raw_affiliation_strings":["Federal University of Rio de Janeiro, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Rio de Janeiro, Brazil","institution_ids":["https://openalex.org/I122140584"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8394,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.78590483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"179","last_page":"188"},"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":0.9991000294685364,"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":0.9991000294685364,"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":0.9785000085830688,"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/T10731","display_name":"Educational Games and Gamification","score":0.9649999737739563,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6797793507575989},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.6365075707435608},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5133039355278015},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49642592668533325},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.42072999477386475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3781583309173584},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3252485990524292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1374921202659607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797793507575989},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.6365075707435608},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5133039355278015},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49642592668533325},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.42072999477386475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3781583309173584},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3252485990524292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1374921202659607},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3450613.3456831","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3450613.3456831","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G7031523853","display_name":"CRII: III: Modeling Student Knowledge and Improving Performance when Learning from Multiple Types of Materials","funder_award_id":"1755910","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W123693119","https://openalex.org/W160448112","https://openalex.org/W650350307","https://openalex.org/W1500188831","https://openalex.org/W1596401170","https://openalex.org/W1959691478","https://openalex.org/W2015040676","https://openalex.org/W2042200273","https://openalex.org/W2054141820","https://openalex.org/W2126917700","https://openalex.org/W2137245235","https://openalex.org/W2338445680","https://openalex.org/W2340952835","https://openalex.org/W2559094423","https://openalex.org/W2574485715","https://openalex.org/W2603824136","https://openalex.org/W2734246064","https://openalex.org/W2805035427","https://openalex.org/W2921387835","https://openalex.org/W2966203649","https://openalex.org/W2979516172","https://openalex.org/W3037878569","https://openalex.org/W3043869244","https://openalex.org/W3046782012","https://openalex.org/W3108291274","https://openalex.org/W4230150613"],"related_works":["https://openalex.org/W2950186459","https://openalex.org/W2170114491","https://openalex.org/W2897298721","https://openalex.org/W2242624680","https://openalex.org/W2136127937","https://openalex.org/W4290987221","https://openalex.org/W2216309014","https://openalex.org/W2569661359","https://openalex.org/W3199841771","https://openalex.org/W4286971555"],"abstract_inverted_index":{"Knowledge":[0],"Tracing":[1],"(KT),":[2],"which":[3],"aims":[4],"to":[5,43,56,75,155,206,260],"model":[6,27,57,76],"student":[7,34,77,81,117,146,209,215,228,268],"knowledge":[8,35,58,78,139,197,216,285],"level":[9],"and":[10,28,141,199,240,287],"predict":[11],"their":[12],"performance,":[13],"is":[14,133],"one":[15],"of":[16,21,33,39,164,179,257,267],"the":[17,49,128,152,171,242,254,261,265,279,295],"most":[18],"important":[19,193],"applications":[20],"user":[22],"modeling.":[23],"Modern":[24],"KT":[25,52],"approaches":[26,53,71],"maintain":[29],"an":[30],"up-to-date":[31],"state":[32],"over":[36],"a":[37,156,213],"set":[38],"course":[40],"concepts":[41,126,166,243,293],"according":[42],"students\u2019":[44,196,236,283],"historical":[45],"performance":[46,237,256,269],"in":[47,65,100,114,137,144,169,194,238,245,264,289,294],"attempting":[48],"problems.":[50,296],"However,":[51,119],"were":[54,72],"designed":[55],"by":[59,79],"observing":[60,80],"relatively":[61],"small":[62],"problem-solving":[63],"steps":[64],"Intelligent":[66],"Tutoring":[67],"Systems.":[68],"While":[69],"these":[70],"applied":[73],"successfully":[74],"solutions":[82],"for":[83,95,120],"simple":[84],"problems,":[85],"such":[86],"as":[87],"multiple-choice":[88],"questions,":[89],"they":[90,159,174],"do":[91],"not":[92,161,188],"perform":[93],"well":[94],"modeling":[96],"complex":[97,121,291],"problem":[98,109,157,172],"solving":[99],"students.":[101],"Most":[102],"importantly,":[103],"current":[104,116],"models":[105],"assume":[106],"that":[107,123,158,173,187,225,230,275],"all":[108,163,178,189],"attempts":[110,190,201,229],"are":[111,191],"equally":[112],"valuable":[113],"quantifying":[115],"knowledge.":[118],"problems":[122,239],"involve":[124],"many":[125],"at":[127],"same":[129],"time,":[130],"this":[131,183],"assumption":[132],"deficient.":[134],"It":[135],"results":[136],"inaccurate":[138],"states":[140,286],"unnecessary":[142,280],"fluctuations":[143,281],"estimated":[145],"knowledge,":[147],"especially":[148],"if":[149],"students":[150],"guess":[151],"correct":[153],"answer":[154],"have":[160,175],"mastered":[162,177],"its":[165,180],"or":[167],"slip":[168],"answering":[170],"already":[176],"concepts.":[181],"In":[182],"paper,":[184],"we":[185],"argue":[186],"equivalently":[192],"discovering":[195,241,290],"state,":[198],"some":[200],"can":[202,231],"be":[203,232],"summarized":[204],"together":[205],"better":[207],"represent":[208],"performance.":[210],"We":[211],"propose":[212],"novel":[214],"tracing":[217],"approach,":[218],"Granular":[219],"RAnk":[220],"based":[221],"TEnsor":[222],"factorization":[223],"(GRATE),":[224],"dynamically":[226],"selects":[227],"aggregated":[233],"while":[234],"predicting":[235],"presented":[244],"them.":[246],"Our":[247,271],"experiments":[248],"on":[249],"three":[250],"real-world":[251],"datasets":[252],"demonstrate":[253],"improved":[255],"GRATE,":[258],"compared":[259],"state-of-the-art":[262],"baselines,":[263],"task":[266],"prediction.":[270],"further":[272],"analysis":[273],"shows":[274],"attempt":[276],"aggregation":[277],"eliminates":[278],"from":[282],"discovered":[284],"helps":[288],"latent":[292]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}