{"id":"https://openalex.org/W4407583865","doi":"https://doi.org/10.1145/3712065","title":"ELF: Educational LLM Framework of Improving and Evaluating AI-generated Content for Classroom Teaching","display_name":"ELF: Educational LLM Framework of Improving and Evaluating AI-generated Content for Classroom Teaching","publication_year":2025,"publication_date":"2025-02-14","ids":{"openalex":"https://openalex.org/W4407583865","doi":"https://doi.org/10.1145/3712065"},"language":"en","primary_location":{"id":"doi:10.1145/3712065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712065","pdf_url":null,"source":{"id":"https://openalex.org/S110189822","display_name":"Journal of Data and Information Quality","issn_l":"1936-1955","issn":["1936-1955","1936-1963"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Data and Information Quality","raw_type":"journal-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/A5114137527","display_name":"Kehui Tan","orcid":"https://orcid.org/0009-0001-5241-9028"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kehui Tan","raw_affiliation_strings":["South China Normal University","South China Normal University,  Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-5241-9028","affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University,  Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiayang Yao","orcid":"https://orcid.org/0009-0006-8560-1631"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayang Yao","raw_affiliation_strings":["South China Normal University","South China Normal University,  Guangzhou China"],"raw_orcid":"https://orcid.org/0009-0006-8560-1631","affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University,  Guangzhou China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043537106","display_name":"Tianqi Pang","orcid":"https://orcid.org/0009-0005-2639-7813"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianqi Pang","raw_affiliation_strings":["South China Normal University","South China Normal University,  Guangzhou China"],"raw_orcid":"https://orcid.org/0009-0005-2639-7813","affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University,  Guangzhou China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064015146","display_name":"Chenyou Fan","orcid":"https://orcid.org/0000-0002-9835-8507"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyou Fan","raw_affiliation_strings":["South China Normal University","South China Normal University,  Guangzhou China"],"raw_orcid":"https://orcid.org/0000-0002-9835-8507","affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University,  Guangzhou China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087201576","display_name":"Yu Song","orcid":"https://orcid.org/0000-0001-5761-5477"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Song","raw_affiliation_strings":["South China Normal University","South China Normal University,  Guangzhou China"],"raw_orcid":"https://orcid.org/0000-0001-5761-5477","affiliations":[{"raw_affiliation_string":"South China Normal University","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Normal University,  Guangzhou China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":null,"apc_paid":null,"fwci":70.6374,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.99915907,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"17","issue":"3","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9833999872207642,"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/T10028","display_name":"Topic Modeling","score":0.9628000259399414,"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":0.7598101496696472},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.4790133833885193},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.3566330671310425},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09412303566932678}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598101496696472},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.4790133833885193},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.3566330671310425},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09412303566932678},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3712065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3712065","pdf_url":null,"source":{"id":"https://openalex.org/S110189822","display_name":"Journal of Data and Information Quality","issn_l":"1936-1955","issn":["1936-1955","1936-1963"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Data and Information Quality","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1975228986","https://openalex.org/W1998827834","https://openalex.org/W2081016604","https://openalex.org/W2081580037","https://openalex.org/W2121112329","https://openalex.org/W2142299132","https://openalex.org/W2475287302","https://openalex.org/W2522074360","https://openalex.org/W2546202826","https://openalex.org/W2762443007","https://openalex.org/W2914304175","https://openalex.org/W2963121203","https://openalex.org/W2966350350","https://openalex.org/W3006100643","https://openalex.org/W3018074695","https://openalex.org/W3096020876","https://openalex.org/W3101638716","https://openalex.org/W3105205406","https://openalex.org/W3111892867","https://openalex.org/W3211457251","https://openalex.org/W4292581785","https://openalex.org/W4294631187","https://openalex.org/W4294768175","https://openalex.org/W4296473473","https://openalex.org/W4302434229","https://openalex.org/W4318480794","https://openalex.org/W4362556083","https://openalex.org/W4382567310","https://openalex.org/W4382656966","https://openalex.org/W4387007747","https://openalex.org/W4389010468","https://openalex.org/W4389485341","https://openalex.org/W4389519574","https://openalex.org/W4392240262","https://openalex.org/W4399455976"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recent":[0],"studies":[1,42],"[":[2,16,23,43],"48":[3],",":[4,18],"72":[5],"]":[6,20,45],"have":[7,33],"demonstrated":[8],"that":[9,47,70,89,128,208],"Large":[10],"Language":[11],"Models":[12],"(LLMs),":[13],"like":[14],"ChatGPT":[15],"3":[17],"46":[19],"and":[21,32,52,82,102,134,155,174,200,218],"LLAMA":[22],"59":[24],"],":[25],"can":[26,97],"assist":[27],"with":[28,116,196],"routine":[29],"teaching":[30,75,103,111,126,159,182],"tasks":[31],"the":[34,147,152,163,224],"potential":[35],"to":[36,77,157],"revolutionize":[37],"traditional":[38],"education.":[39],"However,":[40],"other":[41],"35":[44],"highlight":[46],"LLMs":[48],"often":[49],"contain":[50],"inaccuracies":[51],"demonstrate":[53,162],"limited":[54],"effectiveness":[55,164],"in":[56,170,215],"educational":[57,100,230],"contexts.":[58],"To":[59],"address":[60],"this":[61],"issue,":[62],"we":[63],"propose":[64],"a":[65,107],"unified":[66],"Education":[67],"LLM":[68,72],"Framework":[69],"integrates":[71],"into":[73],"classroom":[74,125],"practice":[76],"enrich":[78],"high-quality":[79],"dialogical":[80],"content":[81,177],"teacher-student":[83],"interactions.":[84],"Unlike":[85],"complex":[86],"data-driven":[87],"models":[88],"require":[90,129],"vast":[91],"amounts":[92],"of":[93,165,227],"data,":[94],"our":[95,117,166,209],"framework":[96],"quickly":[98],"enhance":[99],"engagement":[101],"strategies":[104],"by":[105,189],"utilizing":[106,190],"few":[108],"carefully":[109],"selected":[110],"examples":[112],"from":[113],"master":[114],"teachers":[115],"prompting":[118],"techniques.":[119],"We":[120,161,184],"focus":[121],"on":[122,203],"two":[123,204],"typical":[124],"scenarios":[127],"AI-generated":[130],"content:":[131],"Dialogue":[132,216],"Completion":[133,217],"Expertise":[135,219],"Transfer":[136,220],"Learning.":[137],"The":[138],"former":[139],"scenario":[140,149],"requires":[141,150],"generating":[142,171],"contextually":[143],"appropriate":[144],"dialogues,":[145],"while":[146],"latter":[148],"migrating":[151],"instructional":[153],"styles":[154],"organization":[156],"new":[158],"topics.":[160],"data":[167],"quality-centered":[168],"approach":[169],"semantically":[172],"clear":[173],"factually":[175],"accurate":[176],"as":[178],"organized":[179],"instructions":[180],"for":[181,229],"materials.":[183],"comprehensively":[185],"evaluate":[186],"these":[187],"materials":[188],"Perplexity-based":[191],"Statistical":[192],"Evaluation,":[193],"Human":[194],"Evaluation":[195],"Questionnaires,":[197],"BertScore,":[198],"Rouge,":[199],"BLEU.":[201],"Experiments":[202],"self-collected":[205],"datasets":[206],"show":[207],"method":[210],"significantly":[211],"improves":[212],"various":[213],"metrics":[214],"Learning":[221],"tasks,":[222],"enhancing":[223],"overall":[225],"utility":[226],"AI":[228],"purposes.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
