{"id":"https://openalex.org/W7165518517","doi":"https://doi.org/10.1145/3774398.3811605","title":"How Well Do Large Language Models Recognize Instructional Moves? Establishing Baselines for Foundation Models in Educational Discourse","display_name":"How Well Do Large Language Models Recognize Instructional Moves? Establishing Baselines for Foundation Models in Educational Discourse","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165518517","doi":"https://doi.org/10.1145/3774398.3811605"},"language":null,"primary_location":{"id":"doi:10.1145/3774398.3811605","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774398.3811605","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 Thirteenth ACM Conference on Learning @ Scale","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774398.3811605","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090326226","display_name":"Kirk Vanacore","orcid":"https://orcid.org/0000-0003-0673-5721"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]},{"id":"https://openalex.org/I808010","display_name":"University of Worcester","ror":"https://ror.org/00v6s9648","country_code":"GB","type":"education","lineage":["https://openalex.org/I808010"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Kirk Vanacore","raw_affiliation_strings":["Cornell University, Worcester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0003-0673-5721","affiliations":[{"raw_affiliation_string":"Cornell University, Worcester, NY, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I808010"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071778778","display_name":"Ren\u00e9 F. Kizilcec","orcid":"https://orcid.org/0000-0001-6283-5546"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rene Kizilcec","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-6283-5546","affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"330","last_page":"338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.22830000519752502,"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/T13629","display_name":"Text Readability and Simplification","score":0.22830000519752502,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.08219999819993973,"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/T11587","display_name":"Second Language Acquisition and Learning","score":0.07670000195503235,"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/benchmarking","display_name":"Benchmarking","score":0.5961999893188477},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5701000094413757},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5388000011444092},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.5196999907493591},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5077000260353088},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47749999165534973},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4562999904155731},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45179998874664307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6187000274658203},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5961999893188477},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5701000094413757},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5388000011444092},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.5196999907493591},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5077000260353088},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47749999165534973},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4352000057697296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4293000102043152},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41780000925064087},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.38260000944137573},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C84389358","wikidata":"https://www.wikidata.org/wiki/Q1129466","display_name":"Discourse analysis","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2822999954223633},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27549999952316284},{"id":"https://openalex.org/C36727532","wikidata":"https://www.wikidata.org/wiki/Q861399","display_name":"Educational research","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C188231857","wikidata":"https://www.wikidata.org/wiki/Q2585724","display_name":"Educational assessment","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.26179999113082886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774398.3811605","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774398.3811605","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 Thirteenth ACM Conference on Learning @ Scale","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774398.3811605","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774398.3811605","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 Thirteenth ACM Conference on Learning @ Scale","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8896996378898621,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2019566340","https://openalex.org/W2164777277","https://openalex.org/W4387169527","https://openalex.org/W4388095513","https://openalex.org/W4389995646","https://openalex.org/W4390414972","https://openalex.org/W4392223038","https://openalex.org/W4396831993","https://openalex.org/W4400210641","https://openalex.org/W4400668027","https://openalex.org/W4402118393","https://openalex.org/W4403056940","https://openalex.org/W4403970100","https://openalex.org/W4404073174","https://openalex.org/W4407695830","https://openalex.org/W4408477805","https://openalex.org/W4408504572","https://openalex.org/W4409242813","https://openalex.org/W4413072545","https://openalex.org/W4413224043","https://openalex.org/W4416035743","https://openalex.org/W4416037174","https://openalex.org/W4416337310"],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,75,123],"(LLMs)":[3],"are":[4],"increasingly":[5],"used":[6],"in":[7,30,113,174],"educational":[8,156,182],"contexts,":[9],"yet":[10],"their":[11],"ability":[12,176],"to":[13,80,89,146,170,177],"interpret":[14,178],"authentic":[15],"instructional":[16,28,150],"discourse":[17,157],"out-of-the-box":[18],"remains":[19],"unclear.":[20],"We":[21,40],"benchmark":[22],"six":[23],"state-of-the-art":[24],"LLMs":[25,140],"on":[26],"classifying":[27],"moves":[29],"K-12":[31],"mathematics":[32],"classroom":[33],"transcripts":[34],"annotated":[35],"by":[36],"expert":[37],"educators":[38],"(\u03ba>0.90).":[39],"evaluated":[41],"four":[42],"prompting":[43,58],"strategies,":[44],"including":[45],"zero-shot,":[46],"one-shot,":[47],"and":[48,99,159],"few-shot":[49],"prompts":[50],"derived":[51],"from":[52],"the":[53],"human":[54],"coding":[55],"manual.":[56],"Zero-shot":[57],"achieved":[59],"fair-to-moderate":[60],"agreement":[61],"(\u03ba":[62],"=":[63,66,78,87,105,108],"0.38\u20130.48,":[64],"F1":[65],"0.45\u20130.53).":[67],"Providing":[68],"comprehensive":[69],"examples":[70],"improved":[71],"performance":[72],"for":[73,82,91,121,126,130,155,160],"some":[74],"(e.g.,":[76],"\u03ba":[77,86],"0.48":[79],"0.58":[81],"Claude":[83],"4.5":[84],"Opus;":[85],"0.38":[88],"0.57":[90],"Gemini":[92],"2.5":[93],"Pro),":[94],"but":[95,143],"gains":[96],"were":[97,111],"uneven":[98],"precision":[100,104],"remained":[101],"limited":[102,144],"(best":[103],"0.56,":[106],"recall":[107],"0.75).":[109],"Errors":[110],"concentrated":[112],"constructs":[114],"that":[115,139],"require":[116],"inference":[117],"about":[118],"instructor":[119],"intent;":[120],"example,":[122],"confused":[124],"Press":[125,129],"Reasoning":[127],"with":[128],"Accuracy":[131],"(42%\u201353%":[132],"false-positive":[133],"rates).":[134],"Overall,":[135],"our":[136],"analysis":[137],"found":[138],"demonstrate":[141],"meaningful":[142],"capacity":[145],"identify":[147],"aspects":[148],"of":[149,181],"discourse,":[151],"providing":[152],"a":[153,171],"baseline":[154],"benchmarking":[158],"designing":[161],"more":[162],"reliable":[163],"annotation":[164],"workflows.":[165],"This":[166],"work":[167],"also":[168],"points":[169],"potential":[172],"weakness":[173],"LLMs'":[175],"key":[179],"nuances":[180],"instruction.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-06-23T00:00:00"}