{"id":"https://openalex.org/W4415135128","doi":"https://doi.org/10.1109/tlt.2026.3702387","title":"Dynamic Programming Techniques for Enhancing Cognitive Representation in Knowledge Tracing","display_name":"Dynamic Programming Techniques for Enhancing Cognitive Representation in Knowledge Tracing","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4415135128","doi":"https://doi.org/10.1109/tlt.2026.3702387"},"language":"en","primary_location":{"id":"doi:10.1109/tlt.2026.3702387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2026.3702387","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.02949","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024645274","display_name":"Lixiang Xu","orcid":"https://orcid.org/0000-0001-8946-620X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixiang Xu","raw_affiliation_strings":["Hefei Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0001-8946-620X","affiliations":[{"raw_affiliation_string":"Hefei Institute of Technology","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075391306","display_name":"X. X. Ding","orcid":"https://orcid.org/0009-0007-2024-4087"},"institutions":[{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianwei Ding","raw_affiliation_strings":["Hefei University"],"raw_orcid":"https://orcid.org/0009-0008-9931-8735","affiliations":[{"raw_affiliation_string":"Hefei University","institution_ids":["https://openalex.org/I39774598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001917503","display_name":"Xin Yuan","orcid":"https://orcid.org/0000-0001-5056-171X"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xin Yuan","raw_affiliation_strings":["University of Adelaide"],"raw_orcid":"https://orcid.org/0000-0001-5056-171X","affiliations":[{"raw_affiliation_string":"University of Adelaide","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5143321604","display_name":"Enhong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":"https://orcid.org/0000-0002-4835-4102","affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01263183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"679","last_page":"693"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8640999794006348,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.8640999794006348,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.8026000261306763,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.7117000222206116,"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/cognition","display_name":"Cognition","score":0.6366999745368958},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5758000016212463},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.5680999755859375},{"id":"https://openalex.org/keywords/cognitive-model","display_name":"Cognitive model","score":0.5135999917984009},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.4004000127315521},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.3856000006198883}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7245000004768372},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.6366999745368958},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5758000016212463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5681999921798706},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C161407221","wikidata":"https://www.wikidata.org/wiki/Q4382939","display_name":"Cognitive model","level":3,"score":0.5135999917984009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4318000078201294},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C20854674","wikidata":"https://www.wikidata.org/wiki/Q4386060","display_name":"Cognitive architecture","level":3,"score":0.3765999972820282},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34380000829696655},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.30070000886917114}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tlt.2026.3702387","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2026.3702387","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2506.02949","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.02949","pdf_url":"https://arxiv.org/pdf/2506.02949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2506.02949","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.02949","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.02949","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.02949","pdf_url":"https://arxiv.org/pdf/2506.02949","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3766869091","display_name":null,"funder_award_id":"62176085","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415135128.pdf","grobid_xml":"https://content.openalex.org/works/W4415135128.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Knowledge":[0,99],"Tracing":[1,100],"(KT)":[2],"is":[3,67,205,217,273],"a":[4,121,190],"core":[5],"task":[6],"in":[7],"intelligent":[8],"education.":[9],"It":[10],"aims":[11],"to":[12,61,69,130,160,211,238],"dynamically":[13],"track":[14],"students'":[15,80],"knowledge":[16,258],"mastery":[17],"and":[18,49,84,116,119,127,136,162,166,177,214,266],"predict":[19],"their":[20,25],"learning":[21],"performance":[22,83,126],"based":[23],"on":[24,34,245],"historical":[26],"answering":[27,82,114,170,180,203],"records.":[28],"Most":[29],"existing":[30],"mainstream":[31],"methods":[32],"focus":[33],"static":[35],"feature":[36],"enhancement":[37],"while":[38],"ignoring":[39],"the":[40,71,77,133,141,145,155,164,169,174,179,183,195,202,234,253],"interference":[41],"of":[42,73,79,147,168,198,271],"non-cognitive":[43],"noises":[44],"such":[45],"as":[46],"careless":[47],"errors":[48],"random":[50],"guesses.":[51],"Moreover,":[52],"current":[53],"models":[54],"cannot":[55],"adaptively":[56],"adjust":[57],"cognitive":[58,74,85,200,236,241],"representations":[59,75,237],"according":[60,210],"learners'":[62,199],"individual":[63,212],"differences.":[64],"Therefore,":[65],"it":[66,122],"necessary":[68],"consider":[70],"expressiveness":[72],"from":[76,144],"perspectives":[78],"personalized":[81],"laws.":[86],"To":[87],"address":[88],"these":[89],"issues,":[90],"this":[91],"paper":[92],"proposes":[93],"an":[94,106],"Adaptive":[95,107],"Cognitive":[96,108],"Representation":[97],"Orchestration":[98],"Model":[101],"(AOCR-KT).":[102],"Specifically,":[103],"we":[104,188],"design":[105],"Optimization":[109,192],"Module.":[110,193],"This":[111],"module":[112],"integrates":[113],"status":[115,142,181],"question":[117],"difficulty,":[118],"introduces":[120],"p-mechanism":[123],"involving":[124],"interval":[125,216],"continuity":[128,167],"rules":[129],"compensate":[131],"for":[132],"subjective":[134],"bias":[135],"inaccuracy":[137],"caused":[138],"by":[139],"revising":[140],"only":[143],"perspective":[146],"difficulty.":[148],"The":[149,268],"relevant":[150],"parameters":[151],"are":[152,231],"fed":[153],"into":[154,207],"adaptive":[156],"dynamic":[157],"programming":[158],"algorithm":[159],"judge":[161],"revise":[163],"coherence":[165],"status,":[171],"gradually":[172],"minimize":[173],"cost":[175],"function,":[176],"drive":[178],"toward":[182],"optimal":[184],"solution.":[185],"In":[186],"addition,":[187],"construct":[189],"Partition":[191],"Considering":[194],"staged":[196],"characteristics":[197],"development,":[201],"sequence":[204],"divided":[206],"multiple":[208],"intervals":[209],"differences,":[213],"each":[215],"optimized":[218,235],"independently":[219],"before":[220],"global":[221],"optimization.":[222],"Finally,":[223],"relation":[224],"embeddings":[225],"generated":[226],"via":[227],"bipartite":[228],"graph":[229],"modeling":[230],"fused":[232],"with":[233],"further":[239],"enhance":[240],"expression.":[242],"Extensive":[243],"experiments":[244],"three":[246],"large-scale":[247],"public":[248],"educational":[249],"datasets":[250],"demonstrate":[251],"that":[252],"AOCR-KT":[254,272],"model":[255],"outperforms":[256],"state-of-the-art":[257],"tracing":[259],"models,":[260],"which":[261],"fully":[262],"validates":[263],"its":[264],"effectiveness":[265],"superiority.":[267],"source":[269],"code":[270],"available":[274],"athttps://github.com/bigdata-graph/AOCR-KT.":[275]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-14T00:00:00"}