{"id":"https://openalex.org/W7214065622","doi":"https://doi.org/10.48550/arxiv.2609.25303","title":"Potential for Enhanced Learning in Machine Learning Classes by Using Wiki LLM Indexing","display_name":"Potential for Enhanced Learning in Machine Learning Classes by Using Wiki LLM Indexing","publication_year":2026,"publication_date":"2026-09-21","ids":{"openalex":"https://openalex.org/W7214065622","doi":"https://doi.org/10.48550/arxiv.2609.25303"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.25303","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25303","pdf_url":"https://arxiv.org/pdf/2609.25303","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.25303","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5152540247","display_name":"Brian Wright","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wright, Brian","raw_affiliation_strings":["School of Data Science , University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science , University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5152540247"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.489300012588501,"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":0.489300012588501,"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/T14414","display_name":"Artificial Intelligence in Education","score":0.4417000114917755,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.013500000350177288,"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/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.8029999732971191},{"id":"https://openalex.org/keywords/vector-retrieval","display_name":"vector retrieval","score":0.5799999833106995},{"id":"https://openalex.org/keywords/knowledge-representation","display_name":"knowledge representation","score":0.628000020980835},{"id":"https://openalex.org/keywords/machine-learning-education","display_name":"machine learning education","score":0.6769999861717224},{"id":"https://openalex.org/keywords/contextual-grounding","display_name":"contextual grounding","score":0.6129999756813049},{"id":"https://openalex.org/keywords/syllabus-revision","display_name":"syllabus revision","score":0.6420000195503235},{"id":"https://openalex.org/keywords/ai-assisted-learning","display_name":"AI-assisted learning","score":0.609000027179718}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762499988079071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.682699978351593},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6657999753952026},{"id":"https://openalex.org/C45504901","wikidata":"https://www.wikidata.org/wiki/Q935222","display_name":"Syllabus","level":2,"score":0.6233000159263611},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.542900025844574},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5228999853134155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5127999782562256},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5052000284194946},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.48899999260902405},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3677999973297119},{"id":"https://openalex.org/C2778330532","wikidata":"https://www.wikidata.org/wiki/Q4826577","display_name":"Automatic indexing","level":3,"score":0.36730000376701355},{"id":"https://openalex.org/C156325361","wikidata":"https://www.wikidata.org/wiki/Q1152864","display_name":"Grounded theory","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C141121606","wikidata":"https://www.wikidata.org/wiki/Q8142","display_name":"Currency","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C2780613888","wikidata":"https://www.wikidata.org/wiki/Q6423394","display_name":"Knowledge retrieval","level":3,"score":0.28929999470710754},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.25303","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25303","pdf_url":"https://arxiv.org/pdf/2609.25303","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},{"id":"doi:10.48550/arxiv.2609.25303","doi":"https://doi.org/10.48550/arxiv.2609.25303","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.25303","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.25303","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.25303","pdf_url":"https://arxiv.org/pdf/2609.25303","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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"},"sustainable_development_goals":[{"score":0.9235000014305115,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214065622.pdf","grobid_xml":"https://content.openalex.org/works/W7214065622.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W4387427595","https://openalex.org/W4392933327","https://openalex.org/W4415795858","https://openalex.org/W4417029940","https://openalex.org/W7114889968","https://openalex.org/W7118778125","https://openalex.org/W7161705212","https://openalex.org/W7164945339"],"related_works":["https://openalex.org/W7160887896","https://openalex.org/W7161705212","https://openalex.org/W6885180889","https://openalex.org/W7221114306","https://openalex.org/W7166536747","https://openalex.org/W7151472526","https://openalex.org/W7197374012","https://openalex.org/W7160846889","https://openalex.org/W4415252572","https://openalex.org/W7160964323"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"are":[3,20],"increasingly":[4],"deployed":[5],"as":[6],"course-specific":[7],"tutors,":[8],"but":[9,52,178],"their":[10],"usefulness":[11],"depends":[12],"on":[13,181],"grounding":[14],"in":[15,116,198,251],"vetted":[16],"instructional":[17],"materials":[18],"that":[19,47,53,226,235],"often":[21],"revised":[22],"mid-semester.":[23],"Our":[24],"prior":[25,107],"work":[26],"built":[27],"a":[28,61,66,85,153,162,230],"multimodal":[29],"retrieval-augmented":[30],"generation":[31],"(RAG)":[32],"system":[33],"over":[34,93],"an":[35,94,111,158],"authentic":[36],"machine":[37,236],"learning":[38,237,250],"course":[39,186],"corpus":[40,67,119],"(Foundations":[41],"of":[42,89,176,232,265],"Machine":[43],"Learning)":[44],"and":[45,109,131,148,150,193,205,217],"found":[46],"retrieval":[48,55,202,234],"improved":[49],"contextual":[50],"grounding,":[51],"fixed":[54],"strategies":[56],"were":[57],"suboptimal.":[58],"That":[59],"motivates":[60],"different":[62],"question:":[63],"whether":[64],"how":[65,76],"is":[68,78,120,243],"structured":[69],"at":[70,80,122],"ingest":[71,123],"time":[72],"matters":[73],"more":[74],"than":[75],"much":[77],"retrieved":[79],"query":[81],"time.":[82],"We":[83,137],"present":[84],"controlled":[86],"head-to-head":[87],"comparison":[88],"two":[90],"knowledge":[91],"representations":[92,166],"identical":[95],"classroom":[96],"corpus:":[97],"(A)":[98],"vector":[99],"RAG,":[100],"replicating":[101],"the":[102,118,224],"best-performing":[103],"configuration":[104],"from":[105],"our":[106],"study,":[108],"(B)":[110],"LLM-compiled":[112],"wiki":[113,190],"(Karpathy":[114],"framework),":[115],"which":[117],"synthesized":[121],"into":[124],"linked":[125],"concept":[126,145],"pages":[127],"with":[128],"explicit":[129],"cross-references":[130],"citations":[132,214],"back":[133,222],"to":[134,223,248,261],"source":[135],"materials.":[136],"evaluate":[138],"59":[139],"questions":[140,169,182],"spanning":[141],"single-fact":[142,168],"recall,":[143],"cross-unit":[144],"linking,":[146],"synthesis":[147],"explanation,":[149],"currency":[151],"after":[152],"syllabus":[154],"revision,":[155],"scored":[156,203],"by":[157],"LLM":[159],"judge":[160],"against":[161],"human-authored":[163],"rubric.":[164],"Both":[165],"answered":[167],"about":[170],"equally":[171],"well":[172],"(9.33":[173],"vs.":[174],"9.96":[175],"10),":[177],"diverged":[179],"sharply":[180],"requiring":[183],"links":[184],"across":[185],"units.":[187],"The":[188,212],"compiled":[189],"remained":[191],"accurate":[192],"grounded":[194,197,209],"(9.93;":[195],"100%":[196],"cited":[199],"sources),":[200],"while":[201],"lower":[204],"was":[206],"markedly":[207],"less":[208],"(8.14;":[210],"64%).":[211],"wiki's":[213],"let":[215],"students":[216],"instructors":[218,245],"trace":[219],"any":[220],"claim":[221],"lecture":[225],"introduced":[227],"it,":[228],"adding":[229],"layer":[231],"dynamic":[233],"courses":[238,253],"require.":[239],"While":[240],"further":[241],"testing":[242],"needed,":[244],"using":[246],"AI":[247],"support":[249,262],"ML":[252],"should":[254],"consider":[255],"wiki-based":[256],"structure":[257],"for":[258],"its":[259],"potential":[260],"foundational":[263],"elements":[264],"best":[266],"practice.":[267]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-24T00:00:00"}
