{"id":"https://openalex.org/W4411740539","doi":"https://doi.org/10.3390/e27070685","title":"A Dual-Encoder Contrastive Learning Model for Knowledge Tracing","display_name":"A Dual-Encoder Contrastive Learning Model for Knowledge Tracing","publication_year":2025,"publication_date":"2025-06-26","ids":{"openalex":"https://openalex.org/W4411740539","doi":"https://doi.org/10.3390/e27070685","pmid":"https://pubmed.ncbi.nlm.nih.gov/40724402"},"language":"en","primary_location":{"id":"doi:10.3390/e27070685","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27070685","pdf_url":"https://www.mdpi.com/1099-4300/27/7/685/pdf?version=1751002790","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/27/7/685/pdf?version=1751002790","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075434685","display_name":"Yanhong Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhong Bai","raw_affiliation_strings":["Laboratory of AI for Education, East China Normal University, Shanghai 200062, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of AI for Education, East China Normal University, Shanghai 200062, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043728985","display_name":"Xingjiao Wu","orcid":"https://orcid.org/0000-0001-9146-051X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingjiao Wu","raw_affiliation_strings":["School of Pharmacy, East China Normal University, Shanghai 200062, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Pharmacy, East China Normal University, Shanghai 200062, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006152794","display_name":"Tingjiang Wei","orcid":"https://orcid.org/0000-0001-7809-6901"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tingjiang Wei","raw_affiliation_strings":["Laboratory of AI for Education, East China Normal University, Shanghai 200062, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of AI for Education, East China Normal University, Shanghai 200062, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010540039","display_name":"Liang He","orcid":"https://orcid.org/0000-0002-4723-5486"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai 200062, China"],"raw_orcid":"https://orcid.org/0000-0002-4723-5486","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai 200062, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5006152794"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":2.4083,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89808975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"27","issue":"7","first_page":"685","last_page":"685"},"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":0.9979000091552734,"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":0.9979000091552734,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9933000206947327,"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":0.987500011920929,"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":0.693679690361023},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6478952169418335},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5514340996742249},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.5255045890808105},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5158073902130127},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48622527718544006},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4834045469760895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4068230986595154},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3911011219024658},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33470964431762695},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09135019779205322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.693679690361023},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6478952169418335},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5514340996742249},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.5255045890808105},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5158073902130127},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48622527718544006},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4834045469760895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4068230986595154},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3911011219024658},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33470964431762695},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09135019779205322},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e27070685","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27070685","pdf_url":"https://www.mdpi.com/1099-4300/27/7/685/pdf?version=1751002790","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:40724402","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40724402","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:7057a5ec43c94dcd931b8076faf80f76","is_oa":true,"landing_page_url":"https://doaj.org/article/7057a5ec43c94dcd931b8076faf80f76","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 27, Iss 7, p 685 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12294018","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12294018","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e27070685","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e27070685","pdf_url":"https://www.mdpi.com/1099-4300/27/7/685/pdf?version=1751002790","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8100000023841858}],"awards":[{"id":"https://openalex.org/G6619303971","display_name":null,"funder_award_id":"62207013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411740539.pdf","grobid_xml":"https://content.openalex.org/works/W4411740539.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W650350307","https://openalex.org/W2015040676","https://openalex.org/W2559094423","https://openalex.org/W2900028591","https://openalex.org/W2917551568","https://openalex.org/W2980472839","https://openalex.org/W3005680577","https://openalex.org/W3035442578","https://openalex.org/W3035524453","https://openalex.org/W3043869244","https://openalex.org/W3082341085","https://openalex.org/W3093893125","https://openalex.org/W3102281445","https://openalex.org/W3117062170","https://openalex.org/W3134371412","https://openalex.org/W3167554351","https://openalex.org/W3196654640","https://openalex.org/W3197400233","https://openalex.org/W3217610966","https://openalex.org/W4210707990","https://openalex.org/W4224316526","https://openalex.org/W4282921621","https://openalex.org/W4287888414","https://openalex.org/W4307561542","https://openalex.org/W4313342472","https://openalex.org/W4313398922","https://openalex.org/W4367047438","https://openalex.org/W4383890464","https://openalex.org/W4387124139","https://openalex.org/W4388125279","https://openalex.org/W4390042106","https://openalex.org/W4391233745","https://openalex.org/W4393148022","https://openalex.org/W4393153153","https://openalex.org/W4396967771","https://openalex.org/W4399565317","https://openalex.org/W4400526043","https://openalex.org/W4401536461","https://openalex.org/W4401540305","https://openalex.org/W4403578219","https://openalex.org/W4403582639","https://openalex.org/W4405093247","https://openalex.org/W4405778682","https://openalex.org/W4407989187","https://openalex.org/W4409196450","https://openalex.org/W4409311784","https://openalex.org/W6621483976","https://openalex.org/W6755573351","https://openalex.org/W6765830420"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2888673113","https://openalex.org/W2056065966","https://openalex.org/W2352602608","https://openalex.org/W2062641654","https://openalex.org/W2212288070","https://openalex.org/W3149975758","https://openalex.org/W4390516098","https://openalex.org/W1517786189","https://openalex.org/W3134175397"],"abstract_inverted_index":{"Knowledge":[0,54],"tracing":[1],"(KT)":[2],"models":[3],"learners'":[4],"evolving":[5],"knowledge":[6,36,44,63,112,123],"states":[7],"to":[8,144,162],"predict":[9],"future":[10],"performance,":[11],"serving":[12],"as":[13],"a":[14,57,72,135],"fundamental":[15],"component":[16],"in":[17,30,130,151,190,194],"personalized":[18],"education":[19],"systems.":[20],"However,":[21],"existing":[22,180],"methods":[23],"suffer":[24],"from":[25],"data":[26,68,83,117],"sparsity":[27],"challenges,":[28],"resulting":[29],"inadequate":[31],"representation":[32,65,108,192],"quality":[33],"for":[34,110],"low-frequency":[35,111],"concepts":[37,113,150],"and":[38,168],"inconsistent":[39],"modeling":[40],"of":[41,186],"students'":[42],"actual":[43],"states.":[45],"To":[46,126],"address":[47],"this":[48],"challenge,":[49],"we":[50],"propose":[51],"Dual-Encoder":[52],"Contrastive":[53],"Tracing":[55],"(DECKT),":[56],"contrastive":[58,101],"learning":[59],"framework":[60],"that":[61,120,140,176],"improves":[62],"state":[64],"under":[66],"sparse":[67,195],"conditions.":[69],"DECKT":[70,133,177],"employs":[71],"momentum-updated":[73],"dual-encoder":[74],"architecture":[75],"where":[76],"the":[77,85,152,184,187],"primary":[78],"encoder":[79,87],"processes":[80],"current":[81],"input":[82],"while":[84],"momentum":[86],"maintains":[88],"stable":[89],"historical":[90],"representations":[91],"through":[92,103],"exponential":[93],"moving":[94],"average":[95],"updates.":[96],"These":[97],"encoders":[98],"naturally":[99],"form":[100],"pairs":[102],"temporal":[104],"evolution,":[105],"effectively":[106],"enhancing":[107,165],"capabilities":[109],"without":[114],"requiring":[115],"destructive":[116],"augmentation":[118],"operations":[119],"may":[121],"compromise":[122],"structure":[124,137],"integrity.":[125],"preserve":[127],"semantic":[128],"consistency":[129],"learned":[131],"representations,":[132],"incorporates":[134],"graph":[136],"constraint":[138],"loss":[139],"leverages":[141],"concept-question":[142],"relationships":[143],"maintain":[145],"appropriate":[146],"similarities":[147],"between":[148],"related":[149],"embedding":[153,163],"space.":[154],"Furthermore,":[155],"an":[156],"adversarial":[157],"training":[158],"mechanism":[159],"applies":[160],"perturbations":[161],"vectors,":[164],"model":[166],"robustness":[167],"generalization.":[169],"Extensive":[170],"experiments":[171],"on":[172],"benchmark":[173],"datasets":[174],"demonstrate":[175],"significantly":[178],"outperforms":[179],"state-of-the-art":[181],"methods,":[182],"validating":[183],"effectiveness":[185],"proposed":[188],"approach":[189],"alleviating":[191],"challenges":[193],"educational":[196],"data.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2025-10-10T00:00:00"}
