{"id":"https://openalex.org/W7129291365","doi":"https://doi.org/10.1109/tlt.2026.3665740","title":"Improving Automated Feedback Systems for Tutor Training in Low-Resource Scenarios Through Data Augmentation","display_name":"Improving Automated Feedback Systems for Tutor Training in Low-Resource Scenarios Through Data Augmentation","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7129291365","doi":"https://doi.org/10.1109/tlt.2026.3665740"},"language":null,"primary_location":{"id":"doi:10.1109/tlt.2026.3665740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2026.3665740","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","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/A5111255531","display_name":"Chentianye Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chentianye Xu","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0009-0007-3444-1719","affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110753897","display_name":"Han","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jionghao Lin","raw_affiliation_strings":["Faculty of Education, The University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-3320-3907","affiliations":[{"raw_affiliation_string":"Faculty of Education, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126232724","display_name":"Yujing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yujing Zhang","raw_affiliation_strings":["Faculty of Education, The University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0009-0009-3324-2501","affiliations":[{"raw_affiliation_string":"Faculty of Education, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004225142","display_name":"Tongshuang Wu","orcid":"https://orcid.org/0000-0003-1630-0588"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tongshuang Wu","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-1630-0588","affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Vincent Aleven","orcid":"https://orcid.org/0000-0002-1581-6657"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vincent Aleven","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1581-6657","affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126238067","display_name":"Kenneth R. Koedinger","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kenneth R. Koedinger","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-5850-4768","affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5111255531"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32806511,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"166","last_page":"181"},"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":0.8733999729156494,"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":0.8733999729156494,"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":0.01730000041425228,"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/T11492","display_name":"Academic integrity and plagiarism","score":0.013799999840557575,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/praise","display_name":"Praise","score":0.9659000039100647},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.8718000054359436},{"id":"https://openalex.org/keywords/tutor","display_name":"TUTOR","score":0.6556000113487244},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5105000138282776},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.3928000032901764},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3799000084400177},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3495999872684479}],"concepts":[{"id":"https://openalex.org/C2775868214","wikidata":"https://www.wikidata.org/wiki/Q1208425","display_name":"Praise","level":2,"score":0.9659000039100647},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.8718000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.808899998664856},{"id":"https://openalex.org/C2778371403","wikidata":"https://www.wikidata.org/wiki/Q7672049","display_name":"TUTOR","level":2,"score":0.6556000113487244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5421000123023987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5108000040054321},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5105000138282776},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3928000032901764},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C159456220","wikidata":"https://www.wikidata.org/wiki/Q667334","display_name":"Instructional design","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C154446701","wikidata":"https://www.wikidata.org/wiki/Q4209964","display_name":"Fagan inspection","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2515999972820282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tlt.2026.3665740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tlt.2026.3665740","pdf_url":null,"source":{"id":"https://openalex.org/S130363450","display_name":"IEEE Transactions on Learning Technologies","issn_l":"1939-1382","issn":["1939-1382","2372-0050"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Learning Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6191586256027222}],"awards":[{"id":"https://openalex.org/G8707419170","display_name":null,"funder_award_id":"10851","funder_id":"https://openalex.org/F4320306185","funder_display_name":"Richard King Mellon Foundation"}],"funders":[{"id":"https://openalex.org/F4320306185","display_name":"Richard King Mellon Foundation","ror":"https://ror.org/03qevzg44"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Tutoring":[0],"is":[1,94],"an":[2,215],"effective":[3,200],"instructional":[4],"method":[5],"for":[6,26,48,63,91,130,175,181,234,261],"enhancing":[7],"student":[8],"learning,":[9],"yet":[10],"its":[11],"success":[12],"relies":[13],"on":[14,99,147,214,292],"the":[15,20,27,104,111,115,160,166,186,194,203,221,228,250,290,306],"skill":[16],"and":[17,69,97,178,244,285,304],"experience":[18],"of":[19,30,53,88,117,152,162,205,218,240,299,309],"tutors.":[21,36,54],"This":[22,280],"reliance":[23,291],"presents":[24],"challenges":[25,105],"widespread":[28],"implementation":[29],"tutoring,":[31],"particularly":[32],"in":[33,73,159,227,242,246,277],"training":[34,40,50,76,302],"novice":[35],"To":[37,102],"support":[38],"tutor":[39,75,301],"programs,":[41],"real-time":[42],"automated":[43,300],"feedback":[44],"systems":[45,303],"are":[46],"essential":[47],"efficiently":[49],"large":[51],"numbers":[52],"A":[55],"recent":[56],"study":[57,113],"employed":[58],"Generative":[59],"Pre-Trained":[60],"Transformers":[61],"(GPT)":[62],"sequence":[64],"labeling":[65],"to":[66,126,185,202,249,288],"identify":[67],"desirable":[68],"undesirable":[70],"praise":[71,163,177,183,207],"components":[72],"a":[74,85,138,148,224,283],"dataset,":[77],"providing":[78],"explanatory":[79],"feedback.":[80],"However,":[81],"this":[82],"approach":[83,198,281],"requires":[84],"significant":[86],"amount":[87],"labeled":[89,132],"data":[90,109,191,196,255,265],"fine-tuning,":[92],"which":[93],"both":[95],"labor-intensive":[96],"dependent":[98],"expert":[100],"input.":[101],"address":[103],"associated":[106],"with":[107],"extensive":[108,293],"labeling,":[110],"current":[112],"explores":[114],"use":[116],"prompting":[118,270],"more":[119],"advanced":[120],"GPT":[121,268],"models":[122],"such":[123],"as":[124],"GPT-4o":[125],"generate":[127],"synthetic":[128,264],"datasets":[129],"augmenting":[131],"response":[133],"data,":[134,295],"followed":[135],"by":[136,173,179,238],"fine-tuning":[137,145],"GPT-3.5":[139,146],"model.":[140],"Our":[141],"results":[142],"show":[143],"that":[144,260],"GPT-4o-generated":[149],"augmented":[150,216],"dataset":[151,217],"520":[153,219],"instances":[154],"yields":[155],"statistically":[156],"meaningful":[157],"improvements":[158],"identification":[161,204],"components.":[164],"Specifically,":[165],"<inline-formula":[167,229],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[168,230],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[169,231],"notation=\"LaTeX\">$F_{2}$</tex-math></inline-formula>":[170,232],"score":[171,233],"increases":[172,239],"20.5%":[174],"effort-based":[176],"17.3%":[180],"outcome-based":[182],"relative":[184,248],"same":[187,251],"model":[188,222,252,269,275],"fine-tuned":[189,213,253,274],"without":[190,254],"augmentation.":[192,256],"Moreover,":[193],"proposed":[195],"augmentation":[197],"exhibits":[199],"generalizability":[201],"additional":[206],"categories,":[208],"specifically":[209],"person-based":[210,235],"praise.":[211],"When":[212],"instances,":[220],"achieves":[223],"16.5%":[225],"improvement":[226],"praise,":[236],"accompanied":[237],"19.9%":[241],"M-IoU":[243],"21.6%":[245],"IoU,":[247],"These":[257],"findings":[258],"suggest":[259],"data-intensive":[262],"tasks,":[263],"generated":[266],"through":[267],"can":[271],"substantially":[272],"enhance":[273],"performance":[276],"low-resource":[278],"scenarios.":[279],"offers":[282],"scalable":[284],"cost-effective":[286],"solution":[287],"alleviate":[289],"expert-labeled":[294],"enabling":[296],"broader":[297],"adoption":[298],"facilitating":[305],"rapid":[307],"development":[308],"skilled":[310],"tutors":[311],"at":[312],"scale.":[313]},"counts_by_year":[],"updated_date":"2026-03-21T06:30:42.041108","created_date":"2026-02-18T00:00:00"}