{"id":"https://openalex.org/W3190597193","doi":"https://doi.org/10.1145/3505711.3505729","title":"Data Mining for Discovering Cognitive Models of Learning","display_name":"Data Mining for Discovering Cognitive Models of Learning","publication_year":2021,"publication_date":"2021-11-20","ids":{"openalex":"https://openalex.org/W3190597193","doi":"https://doi.org/10.1145/3505711.3505729","mag":"3190597193"},"language":"en","primary_location":{"id":"doi:10.1145/3505711.3505729","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3505711.3505729","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 5th International Conference on Advances in Artificial Intelligence (ICAAI)","raw_type":"proceedings-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/A5101673870","display_name":"Jinjin Zhao","orcid":"https://orcid.org/0000-0002-3407-4257"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jinjin Zhao","raw_affiliation_strings":["Amazon, US"],"affiliations":[{"raw_affiliation_string":"Amazon, US","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024181810","display_name":"Candace Thille","orcid":"https://orcid.org/0000-0002-3830-4806"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Candace Thille","raw_affiliation_strings":["Amazon, US"],"affiliations":[{"raw_affiliation_string":"Amazon, US","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057312282","display_name":"Dawn Zimmaro","orcid":"https://orcid.org/0000-0003-4836-8106"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dawn Zimmaro","raw_affiliation_strings":["Amazon, US"],"affiliations":[{"raw_affiliation_string":"Amazon, US","institution_ids":["https://openalex.org/I1311688040"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101673870"],"corresponding_institution_ids":["https://openalex.org/I1311688040"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10641471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"130","last_page":"139"},"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":0.9983999729156494,"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":0.9983999729156494,"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":0.9951000213623047,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.989799976348877,"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":0.7053083181381226},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.5087774395942688},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.44240453839302063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42792683839797974},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4107281267642975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.389894962310791},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13816773891448975},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.08302456140518188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053083181381226},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.5087774395942688},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44240453839302063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42792683839797974},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4107281267642975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.389894962310791},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13816773891448975},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.08302456140518188},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3505711.3505729","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3505711.3505729","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 5th International Conference on Advances in Artificial Intelligence (ICAAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1481850464","https://openalex.org/W1562092080","https://openalex.org/W1792756357","https://openalex.org/W1987971958","https://openalex.org/W2039552226","https://openalex.org/W2098126593","https://openalex.org/W2118375674","https://openalex.org/W2122538988","https://openalex.org/W2467346710","https://openalex.org/W2999320175","https://openalex.org/W3046366642","https://openalex.org/W3161507725"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"A":[0,20],"cognitive":[1,21,70,98,157,182,197,208,261],"model":[2,22],"is":[3],"a":[4,14,27,33,55,97,140,168,173,186,202,211,216,249],"descriptive":[5],"account":[6,38],"or":[7,18,84],"computational":[8],"representation":[9],"of":[10,23,29,39,47,57,72,82,159,194,199,258,263],"human":[11],"thinking":[12],"about":[13],"given":[15],"concept,":[16],"skill,":[17],"domain.":[19],"learning,":[24],"includes":[25,166],"both":[26,220],"way":[28],"organizing":[30,92],"knowledge":[31,46,61],"within":[32],"subject":[34,49,63,266],"area":[35],"and":[36,44,66,74,91,105,109,136,155,172,180,192,214,223,235],"an":[37,243],"how":[40,133],"humans":[41,134],"develop":[42,69,137],"accurate":[43],"complete":[45],"that":[48,113,178,189,205,239],"area.":[50],"Learning":[51],"designers":[52,116],"engage":[53],"in":[54,148,242,248],"variety":[56],"practices":[58],"to":[59,68,78,89,153],"unpack":[60],"from":[62,124,210],"matter":[64,267],"experts":[65,104],"novices":[67],"models":[71,77,158,179,198,209,262],"learning":[73,115,121,160,162,183,246,251,264],"use":[75],"those":[76],"guide":[79],"the":[80,145,195,207,229,256,259],"design":[81],"instruction":[83],"instructional":[85],"technologies.":[86],"Traditional":[87],"approaches":[88],"eliciting":[90],"knowledge,":[93],"such":[94],"as":[95],"conducting":[96],"task":[99],"analysis":[100,218],"(CTA)":[101],"[14]":[102],"with":[103,127,161,232,265],"novices,":[106],"are":[107,240],"labor-intensive":[108],"require":[110],"specific":[111],"expertise":[112],"many":[114],"do":[117],"not":[118],"have.":[119],"However,":[120],"data":[122],"generated":[123],"learners\u2019":[125],"interaction":[126],"courses,":[128],"can":[129],"provide":[130],"insight":[131],"into":[132],"think":[135],"knowledge.":[138],"As":[139],"continued":[141],"effort,":[142],"we":[143],"extend":[144],"framework":[146,165],"presented":[147],"our":[149],"earlier":[150],"work":[151],"[17]":[152],"discover":[154],"refine":[156],"data.":[163],"The":[164],"1.":[167],"Variational":[169],"Autoencoder":[170],"(VAE)":[171],"Gaussian":[174],"Mixture":[175],"Model":[176],"(GMM)":[177],"clusters":[181],"patterns;":[184],"2.":[185],"multidimensional":[187],"measure":[188],"quantifies":[190],"validity":[191],"reliability":[193],"discovered":[196,260],"learning;":[200],"3.":[201],"topic-based":[203],"solution":[204,231],"interprets":[206],"linguistic":[212],"perspective;":[213],"4.":[215],"simulation-based":[217],"for":[219],"accuracy":[221],"measures":[222],"course":[224],"refinement":[225],"insights.":[226],"We":[227,253],"demonstrate":[228],"end-to-end":[230],"two":[233],"applications":[234],"four":[236],"case":[237],"studies":[238],"deployed":[241],"openly":[244],"navigated":[245],"system":[247],"workforce":[250],"environment.":[252],"also":[254],"report":[255],"usefulness":[257],"expert":[268],"evaluation.":[269]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
