{"id":"https://openalex.org/W4400642930","doi":"https://doi.org/10.1145/3657604.3662029","title":"Automated Quality Assessment of Multimodal Mathematical Stories Generated by Generative Artificial Intelligence","display_name":"Automated Quality Assessment of Multimodal Mathematical Stories Generated by Generative Artificial Intelligence","publication_year":2024,"publication_date":"2024-07-09","ids":{"openalex":"https://openalex.org/W4400642930","doi":"https://doi.org/10.1145/3657604.3662029"},"language":"en","primary_location":{"id":"doi:10.1145/3657604.3662029","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3657604.3662029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh ACM Conference on Learning @ Scale","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/A5037732249","display_name":"Hai Li","orcid":"https://orcid.org/0009-0004-7299-2042"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hai Li","raw_affiliation_strings":["University of Florida, Gainesville, Florida, USA"],"raw_orcid":"https://orcid.org/0009-0004-7299-2042","affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058487354","display_name":"Rui Guo","orcid":"https://orcid.org/0000-0002-1140-6765"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rui Guo","raw_affiliation_strings":["University of Florida, Gainesville, Florida, USA"],"raw_orcid":"https://orcid.org/0000-0002-1140-6765","affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000207892","display_name":"Chenglu Li","orcid":"https://orcid.org/0000-0002-1782-0457"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenglu Li","raw_affiliation_strings":["University of Utah, Salt Lake City, Utah, USA"],"raw_orcid":"https://orcid.org/0000-0002-1782-0457","affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, Utah, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031131748","display_name":"Wanli Xing","orcid":"https://orcid.org/0000-0002-1446-889X"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wanli Xing","raw_affiliation_strings":["University of Florida, Gainesville, Florida, USA"],"raw_orcid":"https://orcid.org/0000-0002-1446-889X","affiliations":[{"raw_affiliation_string":"University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"110","last_page":"121"},"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":0.9919999837875366,"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":0.9919999837875366,"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/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9625999927520752,"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":0.7065110802650452},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6820738911628723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6248509883880615},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5494380593299866},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.5112836360931396},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3368436396121979},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1446087658405304},{"id":"https://openalex.org/keywords/evaluation-methods","display_name":"Evaluation methods","score":0.0709596574306488},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.061684876680374146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7065110802650452},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6820738911628723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6248509883880615},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5494380593299866},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.5112836360931396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3368436396121979},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1446087658405304},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.0709596574306488},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.061684876680374146},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3657604.3662029","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3657604.3662029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eleventh ACM Conference on Learning @ Scale","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":39,"referenced_works":["https://openalex.org/W99334118","https://openalex.org/W368199433","https://openalex.org/W1828703640","https://openalex.org/W1971394121","https://openalex.org/W1978408537","https://openalex.org/W2051431028","https://openalex.org/W2074025956","https://openalex.org/W2123442489","https://openalex.org/W2280538463","https://openalex.org/W2289057071","https://openalex.org/W2313754513","https://openalex.org/W2406717832","https://openalex.org/W2728214432","https://openalex.org/W2739504579","https://openalex.org/W2885693551","https://openalex.org/W2912891145","https://openalex.org/W2914804768","https://openalex.org/W3039496751","https://openalex.org/W3049238057","https://openalex.org/W3153127278","https://openalex.org/W3158641269","https://openalex.org/W3201130866","https://openalex.org/W4200381364","https://openalex.org/W4221068952","https://openalex.org/W4248824488","https://openalex.org/W4252778404","https://openalex.org/W4292182836","https://openalex.org/W4382236714","https://openalex.org/W4382567098","https://openalex.org/W4383181327","https://openalex.org/W4392445324","https://openalex.org/W4392484110","https://openalex.org/W4409375970","https://openalex.org/W6600008909","https://openalex.org/W6600686112","https://openalex.org/W6600763685","https://openalex.org/W6742369748","https://openalex.org/W6815770002","https://openalex.org/W6818723395"],"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":{"Mathematical":[0],"stories":[1,53,85,94,153,191],"have":[2],"demonstrated":[3],"the":[4,8,35,41,68,81,84,145,195,211,226,238,260,277,285],"ability":[5],"to":[6,28,37,50,66,143],"bolster":[7],"motivation":[9],"and":[10,34,73,102,117,136,149,154,169,180,194,201,210,247,273,281],"interest":[11],"of":[12,31,70,83,114,262,288],"students":[13,39],"in":[14,40,151,298],"learning":[15,109,186],"mathematics,":[16],"thereby":[17,291],"exerting":[18],"a":[19,29,60,128,254,268],"positive":[20],"influence":[21],"on":[22,133,276],"their":[23,155],"academic":[24],"performance.":[25],"However,":[26],"due":[27],"lack":[30],"adequate":[32],"resources":[33],"desire":[36],"engage":[38],"creation":[42],"process,":[43],"Generative":[44],"Artificial":[45],"Intelligence":[46],"(GAI)":[47],"is":[48,130,203],"utilized":[49],"generate":[51],"mathematical":[52,93,152,159,166,190,265,299],"accompanied":[54],"by":[55,76,96,121,125,176],"images.":[56],"This":[57],"study":[58],"presents":[59],"framework":[61],"for":[62,86,98,138,189,257,270,295],"automatic":[63],"quality":[64,261],"assessment":[65],"evaluate":[67],"coherence":[69],"multimodal":[71,140,241,264],"text":[72,148,160,167,172,224,244],"images":[74,123,150],"generated":[75,95,120,124],"GAI,":[77],"as":[78,80],"well":[79],"appropriateness":[82],"different":[87],"grade":[88,187,271,286],"levels.":[89],"The":[90],"dataset":[91],"comprises":[92],"GAI":[97,297],"grades":[99,202],"3,":[100],"4,":[101],"5,":[103],"obtained":[104],"from":[105],"an":[106],"American":[107],"online":[108],"platform,":[110],"each":[111],"story":[112],"consisting":[113],"titles,":[115],"bodies,":[116],"image":[118],"illustrations":[119],"GP4,":[122],"DALL-E3.":[126],"Initially,":[127],"method":[129,215,252],"devised":[131],"based":[132],"CLIP":[134],"model":[135],"Mini-GPT4":[137],"extracting":[139],"semantic":[141],"features":[142,161,200],"establish":[144],"relationship":[146],"between":[147,197],"generation":[156],"parameters.":[157],"Subsequently,":[158],"are":[162,234],"designed,":[163],"including":[164],"nine":[165],"attributes":[168],"ten":[170],"traditional":[171,243],"readability":[173,232,245,249],"indicators,":[174,250],"followed":[175],"collinearity":[177],"feature":[178],"selection":[179],"statistical":[181],"testing.":[182],"Finally,":[183],"five":[184],"machine":[185],"regressor":[188],"were":[192],"trained,":[193],"correlation":[196],"these":[198],"19":[199],"explored":[204],"using":[205],"genetic":[206],"algorithm-based":[207],"factor":[208],"mining":[209],"interpretable":[212],"artificial":[213],"intelligence":[214],"SHapley":[216],"Additive":[217],"exPlanations":[218],"(SHAP).":[219],"To":[220],"further":[221],"understand":[222],"advanced":[223],"features,":[225,242],"latest":[227],"natural":[228],"language":[229],"processing":[230],"(NLP)":[231],"indicators":[233],"also":[235],"integrated":[236],"into":[237],"analysis.":[239],"Through":[240],"metrics,":[246],"NLP":[248],"this":[251],"introduces":[253],"novel":[255],"approach":[256],"automatically":[258],"assessing":[259],"GAI-generated":[263],"stories,":[266,290],"providing":[267],"tool":[269],"predictor":[272],"shedding":[274],"light":[275],"factors":[278],"(Image-text":[279],"relevance":[280],"textual":[282],"features)":[283],"influencing":[284],"level":[287],"analyzed":[289],"offering":[292],"new":[293],"insights":[294],"leveraging":[296],"education.":[300]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
