{"id":"https://openalex.org/W4411472046","doi":"https://doi.org/10.1109/access.2025.3582016","title":"Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions","display_name":"Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411472046","doi":"https://doi.org/10.1109/access.2025.3582016"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3582016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3582016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Takeaki Sakabe","orcid":"https://orcid.org/0009-0005-6312-2173"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeaki Sakabe","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan","Department of Computer Science, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, Japan"],"raw_orcid":"https://orcid.org/0009-0005-6312-2173","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]},{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037088437","display_name":"Yuko Sakurai","orcid":"https://orcid.org/0000-0002-0642-3878"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuko Sakurai","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan","Department of Computer Science, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0642-3878","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]},{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Showa-ku, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081820949","display_name":"Emiko Tsutsumi","orcid":"https://orcid.org/0000-0003-3338-8892"},"institutions":[{"id":"https://openalex.org/I204291657","display_name":"Hosei University","ror":"https://ror.org/00bx6dj65","country_code":"JP","type":"education","lineage":["https://openalex.org/I204291657"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Emiko Tsutsumi","raw_affiliation_strings":["Faculty of Science and Engineering, Hosei University, Koganei, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3338-8892","affiliations":[{"raw_affiliation_string":"Faculty of Science and Engineering, Hosei University, Koganei, Tokyo, Japan","institution_ids":["https://openalex.org/I204291657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056709028","display_name":"Satoshi Oyama","orcid":"https://orcid.org/0000-0002-8124-3578"},"institutions":[{"id":"https://openalex.org/I33858575","display_name":"Nagoya City University","ror":"https://ror.org/04wn7wc95","country_code":"JP","type":"education","lineage":["https://openalex.org/I33858575"]},{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Oyama","raw_affiliation_strings":["Graduate School of Data Science, Nagoya City University, Nagoya, Aichi, Japan","Graduate School of Data Science, Nagoya City University, Mizuho-ku, Nagoya, Aichi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-8124-3578","affiliations":[{"raw_affiliation_string":"Graduate School of Data Science, Nagoya City University, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I33858575","https://openalex.org/I60134161"]},{"raw_affiliation_string":"Graduate School of Data Science, Nagoya City University, Mizuho-ku, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I33858575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19068822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"110226","last_page":"110240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14484","display_name":"Technology and Data Analysis","score":0.8011000156402588,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T14484","display_name":"Technology and Data Analysis","score":0.8011000156402588,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7241584062576294},{"id":"https://openalex.org/keywords/item-response-theory","display_name":"Item response theory","score":0.6421281099319458},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49318426847457886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.465293288230896},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09785106778144836},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09553542733192444}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7241584062576294},{"id":"https://openalex.org/C19875794","wikidata":"https://www.wikidata.org/wiki/Q1207340","display_name":"Item response theory","level":3,"score":0.6421281099319458},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49318426847457886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.465293288230896},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09785106778144836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09553542733192444},{"id":"https://openalex.org/C171606756","wikidata":"https://www.wikidata.org/wiki/Q506132","display_name":"Psychometrics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3582016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fa0753e41d6348d591fd600652313029","is_oa":true,"landing_page_url":"https://doaj.org/article/fa0753e41d6348d591fd600652313029","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":"IEEE Access, Vol 13, Pp 110226-110240 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3582016","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582016","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8046501852","display_name":null,"funder_award_id":"JP24K01112","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"},{"id":"https://openalex.org/G8047616428","display_name":null,"funder_award_id":"JP21K19833","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"},{"id":"https://openalex.org/G8063491431","display_name":null,"funder_award_id":"JPMJCR21D1","funder_id":"https://openalex.org/F4320338075","funder_display_name":"Core Research for Evolutional Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"},{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1535520578","https://openalex.org/W2000619651","https://openalex.org/W2001619934","https://openalex.org/W2041616772","https://openalex.org/W2056760934","https://openalex.org/W2112796928","https://openalex.org/W2462751442","https://openalex.org/W2766412091","https://openalex.org/W2784053847","https://openalex.org/W2903782687","https://openalex.org/W2913875100","https://openalex.org/W3045004532","https://openalex.org/W3180355996","https://openalex.org/W3199263016","https://openalex.org/W3217030260","https://openalex.org/W4284698413","https://openalex.org/W4321365943","https://openalex.org/W4323338440","https://openalex.org/W4385571127","https://openalex.org/W4392114204","https://openalex.org/W6604629408","https://openalex.org/W6629687487","https://openalex.org/W6687045409","https://openalex.org/W6730357551","https://openalex.org/W6743688258","https://openalex.org/W6744627333","https://openalex.org/W6751421292","https://openalex.org/W6758800702","https://openalex.org/W6762931180","https://openalex.org/W6780901134"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Machine":[0],"learning":[1,31,60],"has":[2,9,32],"been":[3],"integrated":[4],"into":[5],"numerous":[6,40],"applications":[7],"and":[8,83,136,146,183,224,271],"emerged":[10],"as":[11,143],"one":[12],"of":[13,27,39,71,114,126,179,198,218,268,286],"the":[14,25,37,53,64,69,81,98,112,124,176,180,196,199,222,225,230,255,266,284],"most":[15],"transformative":[16],"technologies":[17],"in":[18,47,90,133,151,235,293],"our":[19,250,263],"daily":[20],"lives.":[21],"In":[22,50],"recent":[23],"years,":[24],"number":[26],"individuals":[28],"studying":[29],"machine":[30,48,59],"grown":[33],"substantially,":[34],"leading":[35],"to":[36,67,95,117,139,185,277],"emergence":[38],"educational":[41,294],"competitions":[42,270],"focused":[43],"on":[44,175],"building":[45],"expertise":[46],"learning.":[49],"these":[51],"competitions,":[52,288],"participants":[54,116,182],"are":[55,172,275],"tasked":[56],"with":[57,165,190,214],"constructing":[58],"(ML)":[61],"models.":[62],"However,":[63],"dataset":[65,82,188,227,248,256,261],"used":[66,132,184],"compare":[68],"performances":[70,220],"competing":[72],"models":[73,208],"is":[74],"often":[75],"selected":[76],"arbitrarily,":[77],"causing":[78],"discrepancies":[79],"between":[80,221],"participants\u2019":[84,99,278],"skill":[85,279],"levels.":[86,280],"This":[87,281],"can":[88],"result":[89],"competition":[91,115,181],"outcomes":[92],"that":[93,110,162,229,273],"fail":[94],"accurately":[96,119],"reflect":[97],"abilities.":[100],"We":[101],"have":[102],"developed":[103],"a":[104,157,187],"framework":[105,252],"for":[106,148,247],"generating":[107],"image":[108,150],"datasets":[109,274],"enable":[111],"abilities":[113],"be":[118],"assessed.":[120],"Specifically,":[121],"we":[122,155,202],"introduce":[123],"use":[125],"item":[127,144],"response":[128],"theory":[129],"(IRT),":[130],"commonly":[131],"test":[134],"creation":[135],"ability":[137,177,192],"assessment,":[138],"estimate":[140],"parameters":[141,213],"such":[142],"discrimination":[145],"difficulty":[147],"each":[149],"existing":[152],"datasets.":[153],"Additionally,":[154],"utilize":[156],"conditional":[158],"variational":[159],"autoencoder":[160],"(CVAE)":[161],"generates":[163],"images":[164],"specific":[166],"parameter":[167,170],"values.":[168,216],"These":[169],"values":[171],"generated":[173,226],"based":[174],"distribution":[178],"generate":[186],"aligned":[189],"their":[191,219,290],"distribution.":[193],"To":[194],"evaluate":[195],"effectiveness":[197],"proposed":[200,251],"framework,":[201],"conduct":[203],"experiments":[204],"using":[205,211],"810":[206],"ML":[207,269],"automatically":[209],"created":[210],"6":[212],"multiple":[215],"Comparison":[217],"original":[223],"showed":[228],"latter":[231],"was":[232],"more":[233],"effective":[234],"differentiating":[236],"model":[237],"performance.":[238],"Unlike":[239],"conventional":[240],"IRT-based":[241],"methods,":[242],"which":[243],"require":[244],"human":[245],"effort":[246],"generation,":[249,262],"fully":[253],"automates":[254],"generation":[257],"process.":[258],"By":[259],"automating":[260],"approach":[264],"streamlines":[265],"organization":[267],"ensures":[272],"well-suited":[276],"automation":[282],"reduces":[283],"challenges":[285],"hosting":[287],"promoting":[289],"broader":[291],"adoption":[292],"settings.":[295]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
