{"id":"https://openalex.org/W7131088536","doi":"https://doi.org/10.1145/3798162","title":"Higher-Order Spiking and Graph Neural Network for Knowledge Tracing","display_name":"Higher-Order Spiking and Graph Neural Network for Knowledge Tracing","publication_year":2026,"publication_date":"2026-02-23","ids":{"openalex":"https://openalex.org/W7131088536","doi":"https://doi.org/10.1145/3798162"},"language":"en","primary_location":{"id":"doi:10.1145/3798162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3798162","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","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/A5103309727","display_name":"Jinru Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinru Hu","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Shaanxi Normal University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0009-0008-2780-9826","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Shaanxi Normal University, Xi\u2019an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126639727","display_name":"Jianrui Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianrui Chen","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, and Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0001-9104-4540","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, and Key Laboratory of Modern Teaching Technology, Ministry of Education, Shaanxi Normal University, Xi\u2019an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126585720","display_name":"Yuxuan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxuan Wang","raw_affiliation_strings":["School of Artificial Intelligence and Computer Science, Shaanxi Normal University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0009-0006-9355-5743","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and Computer Science, Shaanxi Normal University, Xi\u2019an, China","institution_ids":["https://openalex.org/I88830068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126642584","display_name":"Hao Liao","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Liao","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-1223-6996","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1792571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"44","issue":"3","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6820999979972839,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.6820999979972839,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.20309999585151672,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.019500000402331352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/adaptability","display_name":"Adaptability","score":0.6635000109672546},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.6044999957084656},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.578499972820282},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.573199987411499},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.4844000041484833},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43700000643730164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8759999871253967},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.6044999957084656},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.578499972820282},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.573199987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514000058174133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5121999979019165},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.4844000041484833},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38749998807907104},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3160000145435333},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3798162","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3798162","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6148238066","display_name":null,"funder_award_id":"2024A15 15011938","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G6843419074","display_name":null,"funder_award_id":"62273219 and 62276171","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"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1933687796","https://openalex.org/W2559094423","https://openalex.org/W2974328520","https://openalex.org/W3004515714","https://openalex.org/W3043869244","https://openalex.org/W3082341085","https://openalex.org/W3102040318","https://openalex.org/W3154349795","https://openalex.org/W3155422817","https://openalex.org/W3159873208","https://openalex.org/W3165215982","https://openalex.org/W3183719272","https://openalex.org/W3188250490","https://openalex.org/W3190196337","https://openalex.org/W4221026130","https://openalex.org/W4280647645","https://openalex.org/W4285247025","https://openalex.org/W4295788921","https://openalex.org/W4307295769","https://openalex.org/W4309340952","https://openalex.org/W4362691888","https://openalex.org/W4367047438","https://openalex.org/W4388072146","https://openalex.org/W4389778412","https://openalex.org/W4394585879","https://openalex.org/W4400689812","https://openalex.org/W4406141078"],"related_works":[],"abstract_inverted_index":{"Knowledge":[0],"tracing":[1],"aims":[2],"to":[3,53,99,157],"dynamically":[4,134],"track":[5],"and":[6,66,83,93,123,190],"assess":[7],"learners\u2019":[8,174],"mastery":[9],"of":[10,187],"specific":[11],"knowledge":[12],"concepts":[13],"(e.g.,":[14],"item":[15],"taxonomies,":[16],"skill":[17],"hierarchies).":[18],"Integrating":[19],"it":[20],"into":[21],"recommender":[22],"systems":[23],"greatly":[24],"enhances":[25],"model":[26,68],"explainability,":[27],"yet":[28],"current":[29],"models":[30],"either":[31],"overemphasize":[32],"temporal":[33],"dynamics":[34],"or":[35],"overlook":[36],"inter-concept":[37],"spatial":[38,114],"correlations,":[39],"resulting":[40],"in":[41,44,56,162,172],"suboptimal":[42],"performance":[43],"integrated":[45,156],"spatiotemporal":[46],"modeling.":[47],"Such":[48],"disjointed":[49],"designs":[50],"also":[51],"lead":[52],"limited":[54],"adaptability":[55],"long":[57],"learning":[58,137],"sequences,":[59],"poor":[60],"compatibility":[61],"with":[62,130,178],"real-world":[63],"dynamic":[64],"scenarios,":[65],"restricted":[67],"interpretability.":[69],"To":[70],"solve":[71],"these":[72],"problems,":[73],"we":[74],"propose":[75],"an":[76],"A-SGNN":[77],"framework":[78],"fusing":[79],"higher-order":[80],"path":[81],"spiking":[82],"graph":[84,115],"neural":[85],"networks,":[86],"which":[87],"leverages":[88],"Graph":[89],"Convolutional":[90],"Network":[91,96],"(GCN)":[92],"Spiking":[94],"Neural":[95],"(SNN)":[97],"modules":[98],"make":[100],"up":[101],"for":[102],"existing":[103],"shortcomings.":[104],"Specifically,":[105],"a":[106],"Bidirectional":[107],"GCN":[108,189],"module":[109,129],"fully":[110],"captures":[111],"bidirectional":[112],"high-order":[113],"structures":[116],"between":[117],"concepts,":[118],"accurately":[119],"modeling":[120],"multi-knowledge":[121],"relationships":[122],"reducing":[124],"information":[125],"loss.":[126],"An":[127],"SNN":[128,191],"adaptive":[131],"path-finding":[132],"strategy":[133],"optimizes":[135],"individual":[136],"trajectories,":[138],"overcoming":[139],"traditional":[140],"fixed-path":[141],"rigidity,":[142],"while":[143],"its":[144],"membrane":[145],"potential":[146],"decay":[147,153],"simulates":[148],"human":[149],"forgetting.":[150],"A":[151],"time":[152],"factor":[154],"is":[155,195],"better":[158],"capture":[159],"memory":[160],"effects":[161],"learning.":[163],"Experiments":[164],"demonstrate":[165],"that":[166],"our":[167],"method":[168],"outperforms":[169],"state-of-the-art":[170],"approaches":[171],"predicting":[173],"future":[175],"academic":[176],"performance,":[177],"this":[179],"advantage":[180],"deriving":[181],"from":[182],"the":[183,188],"combined":[184],"synergistic":[185],"benefits":[186],"modules.":[192],"Our":[193],"implementation":[194],"publicly":[196],"available":[197],"at:":[198],"https://github.com/jianruichen/A-SGNN":[199],".":[200]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-24T00:00:00"}