{"id":"https://openalex.org/W3196423366","doi":"https://doi.org/10.18293/seke2021-031","title":"Grasping or Forgetting? MAKT: A Dynamic Model via Multi-head Self-Attention for Knowledge Tracing","display_name":"Grasping or Forgetting? MAKT: A Dynamic Model via Multi-head Self-Attention for Knowledge Tracing","publication_year":2021,"publication_date":"2021-07-07","ids":{"openalex":"https://openalex.org/W3196423366","doi":"https://doi.org/10.18293/seke2021-031","mag":"3196423366"},"language":"en","primary_location":{"id":"doi:10.18293/seke2021-031","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-031","pdf_url":"https://doi.org/10.18293/seke2021-031","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.18293/seke2021-031","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079501434","display_name":"Deming Sheng","orcid":"https://orcid.org/0000-0002-4945-4025"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deming Sheng","raw_affiliation_strings":["School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5079501434"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63110339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2021","issue":null,"first_page":"399","last_page":"404"},"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":0.9980000257492065,"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":0.9980000257492065,"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":0.9907000064849854,"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/T10028","display_name":"Topic Modeling","score":0.9883999824523926,"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":0.7344163060188293},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.7295135259628296},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.594214677810669},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.4825931787490845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4249737858772278},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.42148298025131226},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.25863856077194214},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.16456744074821472},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.11204972863197327}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7344163060188293},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.7295135259628296},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.594214677810669},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.4825931787490845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4249737858772278},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42148298025131226},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.25863856077194214},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.16456744074821472},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.11204972863197327},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18293/seke2021-031","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-031","pdf_url":"https://doi.org/10.18293/seke2021-031","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18293/seke2021-031","is_oa":true,"landing_page_url":"http://doi.org/10.18293/seke2021-031","pdf_url":"https://doi.org/10.18293/seke2021-031","source":{"id":"https://openalex.org/S4220650826","display_name":"Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering","issn_l":"2325-9000","issn":["2325-9000","2325-9086"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Software Engineering and Knowledge Engineering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3196423366.pdf","grobid_xml":"https://content.openalex.org/works/W3196423366.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W650350307","https://openalex.org/W1522301498","https://openalex.org/W1995884758","https://openalex.org/W2007754286","https://openalex.org/W2066816090","https://openalex.org/W2078972197","https://openalex.org/W2146856593","https://openalex.org/W2163644476","https://openalex.org/W2194775991","https://openalex.org/W2505213109","https://openalex.org/W2559094423","https://openalex.org/W2574518178","https://openalex.org/W2613904329","https://openalex.org/W2792805964","https://openalex.org/W2805035427","https://openalex.org/W2951443432","https://openalex.org/W2955931418","https://openalex.org/W2963117210","https://openalex.org/W2963403868","https://openalex.org/W2964121744","https://openalex.org/W2964265128","https://openalex.org/W3034772996","https://openalex.org/W3034854756","https://openalex.org/W4230150613","https://openalex.org/W4385245566","https://openalex.org/W6621483976","https://openalex.org/W6652193975","https://openalex.org/W6687483927","https://openalex.org/W6732172084","https://openalex.org/W6737778391","https://openalex.org/W6739901393","https://openalex.org/W6750970412","https://openalex.org/W6772381481"],"related_works":["https://openalex.org/W4289718052","https://openalex.org/W2164121020","https://openalex.org/W2145559838","https://openalex.org/W3116498279","https://openalex.org/W4287549553","https://openalex.org/W3183027292","https://openalex.org/W4310285384","https://openalex.org/W2794885965","https://openalex.org/W2104218666","https://openalex.org/W4362598752"],"abstract_inverted_index":{"The":[0,113],"outbreak":[1],"of":[2,27,34,41,82,145,170,185],"the":[3,25,32,45,51,73,79,83,103,108,142,162,167,173,181],"COVID-19":[4],"pandemic":[5],"arises":[6],"enormous":[7],"attention":[8,143],"to":[9,61,71,123],"online":[10],"education":[11],"then":[12],"knowledge":[13,36,80,99,149,168],"tracking":[14],"is":[15,37,69],"an":[16],"increasingly":[17],"crucial":[18],"task":[19],"with":[20],"its":[21,124],"vigorous":[22],"development.":[23],"However,":[24],"surge":[26],"student":[28,68,148],"historical":[29,156],"interactions":[30,157,164],"and":[31,76,110,127,147,183,192],"lack":[33],"prior":[35],"engendering":[38],"a":[39,67,91,136],"sequence":[40],"issues,":[42,88],"such":[43],"as":[44],"decrease":[46],"in":[47,53,132],"prediction":[48,104],"accuracy":[49],"while":[50],"increase":[52],"training":[54,120],"time.":[55],"Simultaneously,":[56],"most":[57],"existing":[58],"approaches":[59],"fail":[60],"provide":[62],"in-depth":[63],"insights":[64],"into":[65],"why":[66],"likely":[70],"answer":[72],"question":[74],"incorrectly":[75],"what":[77],"affects":[78],"state":[81,169],"student.":[84],"To":[85],"address":[86],"those":[87],"we":[89],"propose":[90],"multi-head":[92,115],"self-attention":[93,116],"model":[94,109],"named":[95],"MAKT":[96,146],"for":[97],"dynamic":[98],"tracing,":[100],"which":[101],"makes":[102],"results":[105],"interpretable":[106],"at":[107],"instance":[111],"level.":[112],"customized":[114],"layer":[117],"has":[118],"high":[119],"efficiency":[121],"owing":[122],"parallelization":[125],"capability":[126],"spends":[128],"about":[129],"6":[130],"seconds":[131],"each":[133],"epoch":[134],"on":[135,177,197],"single":[137],"GPU.":[138],"We":[139],"further":[140],"visualize":[141],"weights":[144],"acquisition":[150],"tracking,":[151],"finding":[152],"that":[153],"not":[154],"all":[155],"are":[158],"equally":[159],"important":[160],"but":[161],"recent":[163],"profoundly":[165],"establish":[166],"students.":[171],"In":[172],"end,":[174],"extensive":[175],"experiments":[176],"three":[178],"datasets":[179],"demonstrate":[180],"robustness":[182],"superiorities":[184],"MAKT,":[186],"improving":[187],"ACC":[188],"by":[189,194],"1.14":[190],"%":[191,196],"AUC":[193],"1.20":[195],"average.":[198]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}