{"id":"https://openalex.org/W4200004272","doi":"https://doi.org/10.3233/web-210458","title":"Graph-based knowledge tracing: Modeling student proficiency using graph neural networks","display_name":"Graph-based knowledge tracing: Modeling student proficiency using graph neural networks","publication_year":2021,"publication_date":"2021-10-28","ids":{"openalex":"https://openalex.org/W4200004272","doi":"https://doi.org/10.3233/web-210458"},"language":"en","primary_location":{"id":"doi:10.3233/web-210458","is_oa":false,"landing_page_url":"https://doi.org/10.3233/web-210458","pdf_url":null,"source":{"id":"https://openalex.org/S4210183871","display_name":"Web Intelligence","issn_l":"2405-6456","issn":["2405-6456","2405-6464"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Web Intelligence","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/A5103775329","display_name":"Nakagawa Hiromi","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiromi Nakagawa","raw_affiliation_strings":["Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063925941","display_name":"Yusuke Iwasawa","orcid":"https://orcid.org/0000-0002-1321-2622"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yusuke Iwasawa","raw_affiliation_strings":["Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074059447","display_name":"Yutaka Matsuo","orcid":"https://orcid.org/0000-0002-2070-4393"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yutaka Matsuo","raw_affiliation_strings":["Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0,\u00a0,\u00a0","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Department of Engineering, The University of Tokyo, Tokyo, Japan. E-mails:\u00a0nakagawa@weblab.t.u-tokyo.ac.jp,\u00a0iwasawa@weblab.t.u-tokyo.ac.jp,\u00a0matsuo@weblab.t.u-tokyo.ac.jp","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103775329"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":1.2592,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.84238861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"19","issue":"1-2","first_page":"87","last_page":"102"},"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":0.9976000189781189,"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":0.9976000189781189,"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":0.9919999837875366,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9912999868392944,"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/tracing","display_name":"Tracing","score":0.7468673586845398},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7246528267860413},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.633354902267456},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4702058434486389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4190688133239746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39130234718322754},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.10957339406013489}],"concepts":[{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.7468673586845398},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7246528267860413},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.633354902267456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4702058434486389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4190688133239746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39130234718322754},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10957339406013489}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/web-210458","is_oa":false,"landing_page_url":"https://doi.org/10.3233/web-210458","pdf_url":null,"source":{"id":"https://openalex.org/S4210183871","display_name":"Web Intelligence","issn_l":"2405-6456","issn":["2405-6456","2405-6464"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Web Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W2015040676","https://openalex.org/W2016589492","https://openalex.org/W2066816090","https://openalex.org/W2125910575","https://openalex.org/W2157331557","https://openalex.org/W2407753593","https://openalex.org/W2559094423","https://openalex.org/W2607167007","https://openalex.org/W2899457523","https://openalex.org/W2947092077","https://openalex.org/W2963091558","https://openalex.org/W3101707147","https://openalex.org/W3104946560","https://openalex.org/W6604435517","https://openalex.org/W6732629455","https://openalex.org/W6765940776"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Recent":[0],"advancements":[1],"in":[2,10,13,109,121],"computer-assisted":[3],"learning":[4],"systems":[5],"have":[6],"caused":[7],"an":[8],"increase":[9],"the":[11,68,89,99,110,113,129,145,159,163],"research":[12],"knowledge":[14,38,56,81,86,90,100,114],"tracing,":[15,57],"wherein":[16],"student":[17,148],"performance":[18,149],"is":[19,117],"predicted":[20],"over":[21],"time.":[22],"Student":[23],"coursework":[24],"can":[25,46],"potentially":[26,143],"be":[27],"structured":[28],"as":[29,41,54,92,103],"a":[30,37,42,62,79,93,104],"graph.":[31],"Incorporating":[32],"this":[33],"graph-structured":[34],"nature":[35],"into":[36],"tracing":[39,82,101],"model":[40],"relational":[43],"inductive":[44],"bias":[45],"improve":[47,144],"its":[48],"performance;":[49],"however,":[50],"previous":[51,160],"methods,":[52,161],"such":[53,61],"deep":[55],"did":[58],"not":[59,118],"consider":[60],"latent":[63],"graph":[64,72,94,115,130],"structure.":[65,131],"Inspired":[66],"by":[67],"recent":[69],"successes":[70],"of":[71,128,147,158,165],"neural":[73],"networks":[74],"(GNNs),":[75],"we":[76,124],"herein":[77],"propose":[78,125],"GNN-based":[80],"method,":[83],"i.e.,":[84],"graph-based":[85],"tracing.":[87],"Casting":[88],"structure":[91,116],"enabled":[95],"us":[96],"to":[97,156],"reformulate":[98],"task":[102],"time-series":[105],"node-level":[106],"classification":[107],"problem":[108],"GNN.":[111],"As":[112],"explicitly":[119],"provided":[120],"most":[122],"cases,":[123],"various":[126],"implementations":[127],"Empirical":[132],"validations":[133],"on":[134],"two":[135],"open":[136],"datasets":[137],"indicated":[138],"that":[139],"our":[140],"method":[141],"could":[142],"prediction":[146],"and":[150],"demonstrated":[151],"more":[152],"interpretable":[153],"predictions":[154],"compared":[155],"those":[157],"without":[162],"requirement":[164],"any":[166],"additional":[167],"information.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
