{"id":"https://openalex.org/W7128789541","doi":"https://doi.org/10.1145/3770761.3777326","title":"AI-Augmented Instruction: Real-Time Misconception Detection","display_name":"AI-Augmented Instruction: Real-Time Misconception Detection","publication_year":2026,"publication_date":"2026-02-13","ids":{"openalex":"https://openalex.org/W7128789541","doi":"https://doi.org/10.1145/3770761.3777326"},"language":null,"primary_location":{"id":"doi:10.1145/3770761.3777326","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3770761.3777326","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 57th ACM Technical Symposium on Computer Science Education V.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3770761.3777326","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116304964","display_name":"Zhixian Christopher Liding","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhixian Christopher Liding","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125956140","display_name":"Michael Osmolovskiy","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Osmolovskiy","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115842045","display_name":"Harshith Lanka","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harshith Lanka","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082689282","display_name":"Nimisha Roy","orcid":"https://orcid.org/0000-0003-2480-9974"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nimisha Roy","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049813786","display_name":"Rodrigo Borela","orcid":"https://orcid.org/0000-0002-1802-8752"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rodrigo Borela","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5116304964"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78673202,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1421","last_page":"1422"},"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":0.5008000135421753,"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":0.5008000135421753,"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/T10533","display_name":"Teaching and Learning Programming","score":0.18129999935626984,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12884","display_name":"Educational Assessment and Pedagogy","score":0.03359999880194664,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"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/workflow","display_name":"Workflow","score":0.6923999786376953},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.590399980545044},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.557699978351593},{"id":"https://openalex.org/keywords/dashboard","display_name":"Dashboard","score":0.5040000081062317},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.460099995136261},{"id":"https://openalex.org/keywords/thematic-analysis","display_name":"Thematic analysis","score":0.4442000091075897},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.3806000053882599}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091000080108643},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6923999786376953},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.590399980545044},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.557699978351593},{"id":"https://openalex.org/C33499554","wikidata":"https://www.wikidata.org/wiki/Q1417134","display_name":"Dashboard","level":2,"score":0.5040000081062317},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C74196892","wikidata":"https://www.wikidata.org/wiki/Q7781188","display_name":"Thematic analysis","level":3,"score":0.4442000091075897},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35370001196861267},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3328000009059906},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.32019999623298645},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3037000000476837},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C136085584","wikidata":"https://www.wikidata.org/wiki/Q910289","display_name":"Overlay","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3770761.3777326","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3770761.3777326","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 57th ACM Technical Symposium on Computer Science Education V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3770761.3777326","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3770761.3777326","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 57th ACM Technical Symposium on Computer Science Education V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.8669272065162659,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2766624855","https://openalex.org/W2783796210","https://openalex.org/W2981974458","https://openalex.org/W3010609871","https://openalex.org/W3138715211","https://openalex.org/W4392564798","https://openalex.org/W4400643326"],"related_works":[],"abstract_inverted_index":{"Enrollments":[0],"in":[1,48,135],"introductory":[2],"computer":[3],"science":[4],"(CS1)":[5],"courses":[6],"continue":[7],"to":[8,15,40,76,89,109,127,140],"rise,":[9],"making":[10],"it":[11],"difficult":[12],"for":[13,61],"instructors":[14,88],"deliver":[16],"rapid,":[17],"individualized":[18],"feedback":[19],"that":[20,34,86,115],"addresses":[21],"students'":[22,45],"misconceptions":[23],"at":[24,144],"scale.":[25,145],"We":[26],"present":[27,44],"an":[28],"analysis":[29],"framework":[30],"and":[31,43,65,74,82,94,112],"instructor":[32],"tool":[33,134],"leverage":[35],"large":[36],"language":[37],"models":[38],"(LLMs)":[39],"classify,":[41],"cluster,":[42],"coding":[46],"errors":[47,78,93],"real":[49],"time.":[50],"Our":[51,102],"approach":[52],"comprises":[53],"two":[54],"main":[55],"contributions:":[56],"(1)":[57],"a":[58,66,84],"prompt-engineered":[59],"workflow":[60],"automatic":[62],"error":[63],"detection":[64],"clustering":[67,105],"pipeline":[68],"using":[69],"universal":[70],"sentence":[71],"encoders,":[72],"KMeans,":[73],"t-SNE":[75],"group":[77],"into":[79],"thematic":[80,104],"clusters;":[81],"(2)":[83],"dashboard":[85,133],"enables":[87],"review":[90],"class-wide,":[91],"LLM-identified":[92],"dynamically":[95],"tailor":[96],"instruction":[97],"toward":[98],"current":[99],"student":[100],"misunderstandings.":[101],"automated":[103],"system":[106],"is":[107,124],"able":[108],"surface":[110],"conceptual":[111],"strategic":[113],"pitfalls":[114],"often":[116],"persist":[117],"beneath":[118],"superficial":[119],"debugging.":[120],"A":[121],"pilot":[122],"study":[123],"being":[125],"conducted":[126],"evaluate":[128],"the":[129,132],"effectiveness":[130],"of":[131],"large-scale":[136],"CS1":[137],"instructional":[138],"settings":[139],"enhance":[141],"active":[142],"learning":[143]},"counts_by_year":[],"updated_date":"2026-02-15T05:58:04.055770","created_date":"2026-02-14T00:00:00"}