{"id":"https://openalex.org/W2084510717","doi":"https://doi.org/10.1145/2723576.2723618","title":"Towards better affect detectors","display_name":"Towards better affect detectors","publication_year":2015,"publication_date":"2015-03-16","ids":{"openalex":"https://openalex.org/W2084510717","doi":"https://doi.org/10.1145/2723576.2723618","mag":"2084510717"},"language":"en","primary_location":{"id":"doi:10.1145/2723576.2723618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2723576.2723618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Learning Analytics And Knowledge","raw_type":"proceedings-article"},"type":"conference-paper","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/A5115602740","display_name":"Yutao Wang","orcid":"https://orcid.org/0000-0003-2422-5143"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yutao Wang","raw_affiliation_strings":["Worcester Polytechnic Institute, Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Massachusetts","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078998782","display_name":"Neil T. Heffernan","orcid":"https://orcid.org/0000-0002-3280-288X"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neil T. Heffernan","raw_affiliation_strings":["Worcester Polytechnic Institute, Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Massachusetts","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049123794","display_name":"Cristina Heffernan","orcid":"https://orcid.org/0009-0009-4114-9892"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cristina Heffernan","raw_affiliation_strings":["Worcester Polytechnic Institute, Massachusetts"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Massachusetts","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"35"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9980000257492065,"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/T10731","display_name":"Educational Games and Gamification","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.8337253332138062},{"id":"https://openalex.org/keywords/boredom","display_name":"Boredom","score":0.8124182224273682},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6749489307403564},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6600626111030579},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.6153528690338135},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5906302332878113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5348317623138428},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4412650167942047},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4336094856262207},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4242517352104187},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.37115734815597534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3460642099380493},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.24582085013389587},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14582297205924988},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08191794157028198}],"concepts":[{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.8337253332138062},{"id":"https://openalex.org/C2777589236","wikidata":"https://www.wikidata.org/wiki/Q34255","display_name":"Boredom","level":2,"score":0.8124182224273682},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6749489307403564},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6600626111030579},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.6153528690338135},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5906302332878113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5348317623138428},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4412650167942047},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4336094856262207},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4242517352104187},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.37115734815597534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3460642099380493},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.24582085013389587},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14582297205924988},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08191794157028198},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2723576.2723618","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2723576.2723618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Learning Analytics And Knowledge","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G7277750199","display_name":null,"funder_award_id":"1252297","funder_id":"https://openalex.org/F4320309617","funder_display_name":"National Foundation for Science and Technology Development"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309617","display_name":"National Foundation for Science and Technology Development","ror":"https://ror.org/04rw64z44"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W179797448","https://openalex.org/W973843712","https://openalex.org/W1811740382","https://openalex.org/W1918776538","https://openalex.org/W1964716415","https://openalex.org/W1978836878","https://openalex.org/W2053154970","https://openalex.org/W2066930759","https://openalex.org/W2117342357","https://openalex.org/W2124480307","https://openalex.org/W2135514714","https://openalex.org/W2157825442","https://openalex.org/W2394824715"],"related_works":["https://openalex.org/W318616257","https://openalex.org/W3118254946","https://openalex.org/W2917043877","https://openalex.org/W3026775601","https://openalex.org/W2035863303","https://openalex.org/W3121061808","https://openalex.org/W2139976611","https://openalex.org/W4386479718","https://openalex.org/W4206918453","https://openalex.org/W4234657158"],"abstract_inverted_index":{"The":[0,49,69,82,95],"well-studied":[1],"Baker":[2],"et":[3],"al.,":[4],"affect":[5,47,67],"detectors":[6,120],"on":[7],"boredom,":[8],"frustration,":[9],"confusion":[10],"and":[11,26],"engagement":[12],"concentration":[13],"with":[14],"ASSISTments":[15],"dataset":[16,61],"were":[17,121],"used":[18],"to":[19,43,62,89],"predict":[20],"state":[21],"tests":[22],"scores,":[23],"college":[24],"enrollment,":[25],"even":[27],"whether":[28],"a":[29,33,72],"student":[30,90,105],"majored":[31],"in":[32,59],"STEM":[34],"field.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39],"present":[40],"three":[41],"attempts":[42],"improve":[44],"upon":[45],"current":[46],"detectors.":[48,68],"first":[50],"attempt":[51,84,97],"analyzed":[52],"the":[53,60,63,66,78,118,125],"effect":[54],"of":[55,65,117],"missing":[56,79],"skill":[57,80],"tags":[58],"accuracy":[64],"results":[70],"show":[71],"small":[73],"improvement":[74],"after":[75],"correctly":[76],"tagging":[77],"values.":[81],"second":[83],"added":[85,98],"four":[86,119],"features":[87,100],"related":[88],"classes":[91],"for":[92,109],"feature":[93,110],"selection.":[94,111],"third":[96],"two":[99,115],"that":[101,114],"described":[102],"information":[103],"about":[104],"common":[106],"wrong":[107],"answers":[108],"Result":[112],"showed":[113],"out":[116],"improved":[122],"by":[123],"adding":[124],"new":[126],"features.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}