{"id":"https://openalex.org/W7125187648","doi":"https://doi.org/10.1145/3785022.3785101","title":"Disagreement as Data: Reasoning Trace Analytics in Multi-Agent Systems","display_name":"Disagreement as Data: Reasoning Trace Analytics in Multi-Agent Systems","publication_year":2026,"publication_date":"2026-04-25","ids":{"openalex":"https://openalex.org/W7125187648","doi":"https://doi.org/10.1145/3785022.3785101"},"language":null,"primary_location":{"id":"doi:10.1145/3785022.3785101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785101","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3785022.3785101","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123503791","display_name":"Elham Tajik","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Elham Tajik","raw_affiliation_strings":["University of Albany, Albany, New York, USA"],"raw_orcid":"https://orcid.org/0009-0007-4716-292X","affiliations":[{"raw_affiliation_string":"University of Albany, Albany, New York, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123485409","display_name":"Conrad Borchers","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":"Conrad Borchers","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0003-3437-8979","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123458568","display_name":"Bahar Shahrokhian","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bahar Shahrokhian","raw_affiliation_strings":["Arizona State University, Tempe, Arizona, USA"],"raw_orcid":"https://orcid.org/0000-0002-3737-4714","affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, Arizona, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123479336","display_name":"Sebastian Simon","orcid":null},"institutions":[{"id":"https://openalex.org/I234216984","display_name":"Universit\u00e9 Nantes Angers Le Mans","ror":"https://ror.org/0406t3m57","country_code":"FR","type":"education","lineage":["https://openalex.org/I234216984"]},{"id":"https://openalex.org/I4210086593","display_name":"Institut Sup\u00e9rieur des Mat\u00e9riaux du Mans","ror":"https://ror.org/001s4x714","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210086593"]},{"id":"https://openalex.org/I4210108471","display_name":"Le Mans Universit\u00e9","ror":"https://ror.org/01mtcc283","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210108471"]},{"id":"https://openalex.org/I4210125982","display_name":"Centre Hospitalier du Mans","ror":"https://ror.org/03bf2nz41","country_code":"FR","type":"healthcare","lineage":["https://openalex.org/I4210125982"]},{"id":"https://openalex.org/I4210167108","display_name":"Centre de Transfert de Technologie du Mans","ror":"https://ror.org/05n3hnq20","country_code":"FR","type":"facility","lineage":["https://openalex.org/I4210167108"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sebastian Simon","raw_affiliation_strings":["Le Mans University, Le Mans, Pays de La Loire, France"],"raw_orcid":"https://orcid.org/0000-0003-3218-2032","affiliations":[{"raw_affiliation_string":"Le Mans University, Le Mans, Pays de La Loire, France","institution_ids":["https://openalex.org/I4210086593","https://openalex.org/I4210125982","https://openalex.org/I234216984","https://openalex.org/I4210108471","https://openalex.org/I4210167108"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101985492","display_name":"Ali Keramati","orcid":"https://orcid.org/0000-0002-4763-7418"},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]},{"id":"https://openalex.org/I4210140791","display_name":"Irvine University","ror":"https://ror.org/04ysmca02","country_code":"US","type":"education","lineage":["https://openalex.org/I4210140791"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Keramati","raw_affiliation_strings":["University of California. Irvine, Irvine, California, USA"],"raw_orcid":"https://orcid.org/0000-0002-4763-7418","affiliations":[{"raw_affiliation_string":"University of California. Irvine, Irvine, California, USA","institution_ids":["https://openalex.org/I204250578","https://openalex.org/I4210140791"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109747019","display_name":"Sonika Pal","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sonika Pal","raw_affiliation_strings":["Indian Institute of Technology, Mumbai, Mumbai, Maharashtra, India"],"raw_orcid":"https://orcid.org/0009-0007-3470-6369","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Mumbai, Mumbai, Maharashtra, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017567414","display_name":"Sreecharan Sankaranarayanan","orcid":"https://orcid.org/0000-0001-9122-6870"},"institutions":[{"id":"https://openalex.org/I4210159998","display_name":"Flagship Pioneering (United States)","ror":"https://ror.org/05r2q5n94","country_code":"US","type":"company","lineage":["https://openalex.org/I4210159998"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sreecharan Sankaranarayanan","raw_affiliation_strings":["Extuitive Inc. (Flagship Pioneering), Cambridge, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0000-0001-9122-6870","affiliations":[{"raw_affiliation_string":"Extuitive Inc. (Flagship Pioneering), Cambridge, Massachusetts, USA","institution_ids":["https://openalex.org/I4210159998"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5123503791"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12491871,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"933","last_page":"939"},"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":0.5626000165939331,"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":0.5626000165939331,"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/T10636","display_name":"Innovative Teaching and Learning Methods","score":0.06970000267028809,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.05810000002384186,"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/coding","display_name":"Coding (social sciences)","score":0.5654000043869019},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.5630000233650208},{"id":"https://openalex.org/keywords/cognitive-reframing","display_name":"Cognitive reframing","score":0.4968000054359436},{"id":"https://openalex.org/keywords/qualitative-reasoning","display_name":"Qualitative reasoning","score":0.4875999987125397},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.47530001401901245},{"id":"https://openalex.org/keywords/analytic-reasoning","display_name":"Analytic reasoning","score":0.45419999957084656},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.43470001220703125},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.42320001125335693},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.42010000348091125},{"id":"https://openalex.org/keywords/qualitative-research","display_name":"Qualitative research","score":0.37450000643730164}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6769000291824341},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5654000043869019},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.5630000233650208},{"id":"https://openalex.org/C187029079","wikidata":"https://www.wikidata.org/wiki/Q958679","display_name":"Cognitive reframing","level":2,"score":0.4968000054359436},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4968000054359436},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.4875999987125397},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.47530001401901245},{"id":"https://openalex.org/C103057564","wikidata":"https://www.wikidata.org/wiki/Q4751139","display_name":"Analytic reasoning","level":3,"score":0.45419999957084656},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.42010000348091125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4009000062942505},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3767000138759613},{"id":"https://openalex.org/C190248442","wikidata":"https://www.wikidata.org/wiki/Q839486","display_name":"Qualitative research","level":2,"score":0.37450000643730164},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C78821406","wikidata":"https://www.wikidata.org/wiki/Q391810","display_name":"Think aloud protocol","level":3,"score":0.35109999775886536},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C2780554381","wikidata":"https://www.wikidata.org/wiki/Q2063340","display_name":"Sensemaking","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C154350673","wikidata":"https://www.wikidata.org/wiki/Q7623615","display_name":"Strict constructionism","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.31619998812675476},{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C87156501","wikidata":"https://www.wikidata.org/wiki/Q7268708","display_name":"Qualitative property","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C2777598771","wikidata":"https://www.wikidata.org/wiki/Q5341279","display_name":"Educational data mining","level":2,"score":0.29420000314712524},{"id":"https://openalex.org/C37228920","wikidata":"https://www.wikidata.org/wiki/Q1307600","display_name":"Experiential learning","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.29330000281333923},{"id":"https://openalex.org/C71008984","wikidata":"https://www.wikidata.org/wiki/Q2890076","display_name":"Rigour","level":2,"score":0.2874000072479248},{"id":"https://openalex.org/C2780224610","wikidata":"https://www.wikidata.org/wiki/Q1530061","display_name":"Credibility","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2599000036716461},{"id":"https://openalex.org/C36727532","wikidata":"https://www.wikidata.org/wiki/Q861399","display_name":"Educational research","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3785022.3785101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785101","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2601.12618","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.12618","pdf_url":"https://arxiv.org/pdf/2601.12618","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3785022.3785101","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785101","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.685942530632019,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Learning":[0],"analytics":[1],"researchers":[2],"often":[3],"analyze":[4],"qualitative":[5,79,160],"student":[6],"data":[7,73],"such":[8,42],"as":[9,32,100],"coded":[10],"annotations":[11],"or":[12],"interview":[13],"transcripts":[14],"to":[15,40,74,85,89,166],"understand":[16],"learning":[17],"processes.":[18],"With":[19],"the":[20,170],"rise":[21],"of":[22,71,109,172,198],"generative":[23],"AI,":[24],"fully":[25],"automated":[26],"and":[27,68,93,130,148,168,204],"human\u2013AI":[28],"workflows":[29,43],"have":[30],"emerged":[31],"promising":[33],"methods":[34],"for":[35,150],"analysis.":[36],"However,":[37],"methodological":[38,202],"standards":[39],"guide":[41],"remain":[44],"limited.":[45],"In":[46],"this":[47,140],"study,":[48],"we":[49,117],"propose":[50],"that":[51,119],"reasoning":[52,87,123],"traces":[53,88],"generated":[54],"by":[55,139,178],"large":[56],"language":[57],"model":[58],"(LLM)":[59],"agents,":[60,97],"especially":[61,182],"within":[62,146],"multi-agent":[63],"systems,":[64],"constitute":[65],"a":[66,101,194],"novel":[67],"rich":[69],"form":[70],"process":[72,171],"enhance":[75],"interpretive":[76,180,205],"practices":[77],"in":[78,207],"coding.":[80],"We":[81,188],"apply":[82],"cosine":[83],"similarity":[84,124,157],"LLM":[86,120],"systematically":[90],"detect,":[91],"quantify,":[92],"interpret":[94],"disagreements":[95,192],"among":[96],"reframing":[98],"disagreement":[99,129],"meaningful":[102],"analytic":[103,199],"signal.":[104],"Analyzing":[105],"nearly":[106],"10,000":[107],"instances":[108],"agent":[110],"pairs":[111],"coding":[112,134,177],"human":[113,133],"tutoring":[114],"dialog":[115],"segments,":[116],"show":[118],"agents\u2019":[121],"semantic":[122],"robustly":[125],"differentiates":[126],"consensus":[127],"from":[128],"correlates":[131],"with":[132,159,186],"reliability.":[135],"Qualitative":[136],"analysis":[137],"guided":[138],"metric":[141],"reveals":[142],"nuanced":[143],"instructional":[144],"sub-functions":[145],"codes":[147],"opportunities":[149],"conceptual":[151],"codebook":[152],"refinement.":[153],"By":[154],"integrating":[155],"quantitative":[156],"metrics":[158],"review,":[161],"our":[162],"method":[163],"bears":[164],"potential":[165],"improve":[167],"accelerate":[169],"establishing":[173],"inter-rater":[174],"reliability":[175],"during":[176],"surfacing":[179],"ambiguity,":[181],"when":[183],"LLMs":[184],"collaborate":[185],"humans.":[187],"discuss":[189],"how":[190],"reasoning-trace":[191],"represent":[193],"valuable":[195],"new":[196],"class":[197],"signals":[200],"advancing":[201],"rigor":[203],"depth":[206],"educational":[208],"research.":[209]},"counts_by_year":[],"updated_date":"2026-04-26T06:07:20.044499","created_date":"2026-01-22T00:00:00"}
