{"id":"https://openalex.org/W7155601930","doi":"https://doi.org/10.1145/3785022.3785091","title":"Learning Analytics for Assessment Preparation: Constructing Graphs to Guide Higher-Order Question Generation","display_name":"Learning Analytics for Assessment Preparation: Constructing Graphs to Guide Higher-Order Question Generation","publication_year":2026,"publication_date":"2026-04-25","ids":{"openalex":"https://openalex.org/W7155601930","doi":"https://doi.org/10.1145/3785022.3785091"},"language":null,"primary_location":{"id":"doi:10.1145/3785022.3785091","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785091","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":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3785022.3785091","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100672403","display_name":"Joel Weijia Lai","orcid":"https://orcid.org/0000-0002-5619-2051"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Joel Weijia Lai","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5619-2051","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101986995","display_name":"Shen Yong Ho","orcid":"https://orcid.org/0000-0003-3843-0324"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shen Yong Ho","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-3843-0324","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048877911","display_name":"Fun Siong Lim","orcid":"https://orcid.org/0000-0001-8887-6047"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Fun Siong Lim","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-8887-6047","affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100672403"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.95436164,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"919","last_page":"925"},"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":0.36800000071525574,"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":0.36800000071525574,"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/T11122","display_name":"Online Learning and Analytics","score":0.10540000349283218,"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":0.04690000042319298,"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/pipeline","display_name":"Pipeline (software)","score":0.5002999901771545},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.498199999332428},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4542999863624573},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4521999955177307},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4438000023365021},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.4277999997138977},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.39410001039505005},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.38850000500679016},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.34450000524520874}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204999923706055},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5090000033378601},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5002999901771545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49880000948905945},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.498199999332428},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4521999955177307},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38190001249313354},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.359499990940094},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.34450000524520874},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3398999869823456},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.30469998717308044},{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C176730311","wikidata":"https://www.wikidata.org/wiki/Q867668","display_name":"Multiple choice","level":3,"score":0.29249998927116394},{"id":"https://openalex.org/C3018615553","wikidata":"https://www.wikidata.org/wiki/Q189293","display_name":"Frequently asked questions","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2818000018596649},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C200287777","wikidata":"https://www.wikidata.org/wiki/Q830115","display_name":"Concept map","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C48164120","wikidata":"https://www.wikidata.org/wiki/Q4491893","display_name":"Concept learning","level":2,"score":0.25589999556541443}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3785022.3785091","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785091","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"}],"best_oa_location":{"id":"doi:10.1145/3785022.3785091","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785022.3785091","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":0.8125120401382446,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W105600248","https://openalex.org/W2047940964","https://openalex.org/W2061504941","https://openalex.org/W2167619573","https://openalex.org/W4399450508","https://openalex.org/W4400210662","https://openalex.org/W4402480692","https://openalex.org/W4403577869","https://openalex.org/W4417300994","https://openalex.org/W4417517075"],"related_works":[],"abstract_inverted_index":{"High-quality":[0],"assessment":[1,33,182,195],"at":[2],"scale":[3],"requires":[4],"questions":[5,34,117],"that":[6,21,106,139,151,187],"are":[7,41,188],"conceptually":[8],"rich,":[9],"appropriately":[10],"difficult,":[11],"and":[12,25,49,71,85,90,120,166,194],"cognitively":[13],"engaging.":[14],"We":[15,113,148],"present":[16],"a":[17,46,50,97,177],"learning":[18,193],"analytics":[19],"pipeline":[20],"transforms":[22],"archival":[23],"assessments":[24],"learner":[26],"performance":[27,73,94],"data":[28],"for":[29,118,190],"question":[30],"generation.":[31],"Past":[32],"from":[35,45],"an":[36,77],"undergraduate":[37],"engineering":[38],"physics":[39],"course":[40],"multi-labelled":[42],"with":[43,92,122,132,145,184],"topics":[44,84],"predefined":[47],"syllabus,":[48],"primary":[51],"large":[52],"language":[53],"model":[54],"(LLM)":[55],"is":[56,176],"selected":[57],"via":[58],"inter-rater":[59],"reliability":[60],"against":[61],"expert":[62,146,172],"judgments":[63],"to":[64,162],"ensure":[65],"label":[66],"quality.":[67],"Using":[68],"these":[69],"labels":[70],"student":[72,93],"data,":[74],"we":[75,137],"construct":[76],"undirected":[78],"weighted":[79],"graph":[80,101],"where":[81],"nodes":[82],"represent":[83],"edges":[86],"capture":[87],"both":[88],"co-occurrence":[89],"difficulty,":[91],"used":[95],"as":[96],"proxy.":[98],"Exploring":[99],"this":[100],"reveals":[102],"difficulty-calibrated":[103],"topic":[104],"sets":[105],"can":[107],"be":[108,163],"retrieved":[109],"around":[110],"target":[111],"topics.":[112,135],"then":[114],"evaluate":[115],"LLM-generated":[116],"difficulty":[119,186],"alignment":[121],"the":[123,133,152,157],"Structure":[124],"of":[125,167,180],"Observed":[126],"Learning":[127],"Outcomes":[128],"taxonomy":[129],"when":[130],"provided":[131],"requested":[134],"Empirically,":[136],"found":[138,150],"GPT-5":[140],"Thinking":[141],"shows":[142],"higher":[143],"agreement":[144],"labels.":[147],"further":[149],"generated":[153],"questions,":[154],"grounded":[155],"by":[156],"topic-performance":[158],"graph,":[159],"were":[160],"deemed":[161],"more":[164],"difficult":[165],"higher-order":[168,181],"intent":[169],"under":[170],"blinded":[171],"review.":[173],"The":[174],"contribution":[175],"scalable":[178],"creation":[179],"items":[183],"appropriate":[185],"imperative":[189],"generative":[191],"personalised":[192],"systems.":[196]},"counts_by_year":[],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2026-04-26T00:00:00"}