{"id":"https://openalex.org/W4407842206","doi":"https://doi.org/10.1145/3706468.3706538","title":"Qualitative Parameter Triangulation: A Conceptual and Methodological Framework for Event-Based Temporal Models","display_name":"Qualitative Parameter Triangulation: A Conceptual and Methodological Framework for Event-Based Temporal Models","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4407842206","doi":"https://doi.org/10.1145/3706468.3706538"},"language":"en","primary_location":{"id":"doi:10.1145/3706468.3706538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3706468.3706538","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 15th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3706468.3706538","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079953215","display_name":"Yeyu Wang","orcid":"https://orcid.org/0000-0003-1978-5453"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yeyu Wang","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0000-0003-1978-5453","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5094131226","display_name":"Zack Carpenter","orcid":"https://orcid.org/0000-0002-5193-7501"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zack Carpenter","raw_affiliation_strings":["University of Minnesota, Minneapolis, Minnesota, USA"],"raw_orcid":"https://orcid.org/0000-0002-5193-7501","affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, Minnesota, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054856064","display_name":"Zachari Swiecki","orcid":"https://orcid.org/0000-0002-7414-5507"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zachari Swiecki","raw_affiliation_strings":["Monash University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-7414-5507","affiliations":[{"raw_affiliation_string":"Monash University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043097802","display_name":"David Williamson Shaffer","orcid":"https://orcid.org/0000-0001-9613-5740"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Williamson Shaffer","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0000-0001-9613-5740","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, Wisconsin, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5965,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7461442,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"537","last_page":"546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12805","display_name":"Cognitive Science and Mapping","score":0.9843000173568726,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9797000288963318,"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/triangulation","display_name":"Triangulation","score":0.6749165058135986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6536005735397339},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5437619686126709},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.41992437839508057},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.3615798354148865},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33327388763427734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3258657157421112},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.10810792446136475},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08661848306655884},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08593133091926575},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06986203789710999}],"concepts":[{"id":"https://openalex.org/C135981907","wikidata":"https://www.wikidata.org/wiki/Q188056","display_name":"Triangulation","level":2,"score":0.6749165058135986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6536005735397339},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5437619686126709},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41992437839508057},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.3615798354148865},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33327388763427734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3258657157421112},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.10810792446136475},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08661848306655884},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08593133091926575},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06986203789710999},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3706468.3706538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3706468.3706538","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 15th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:monash.edu:openaire/6d62266b-afc8-4c84-a1a3-a5a8113986c7","is_oa":true,"landing_page_url":"https://research.monash.edu/en/publications/6d62266b-afc8-4c84-a1a3-a5a8113986c7","pdf_url":"https://researchmgt.monash.edu/ws/files/783800826/742656003-oa.pdf","source":{"id":"https://openalex.org/S4306402625","display_name":"Monash University Research Portal (Monash University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I56590836","host_organization_name":"Monash University","host_organization_lineage":["https://openalex.org/I56590836"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Wang, Y, Carpenter, Z, Swiecki, Z & Shaffer, D W 2025, Qualitative Parameter Triangulation : A Conceptual and Methodological Framework for Event-Based Temporal Models. in A Zamecnik, V Kuvar & A Wong (eds), The Fifteenth International Conference on Learning Analytics & Knowledge. Association for Computing Machinery (ACM), New York NY USA, pp. 537-546, International Conference on Learning Analytics and Knowledge 2025, Dublin, Ireland, 3/03/25. https://doi.org/10.1145/3706468.3706538","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3706468.3706538","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3706468.3706538","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 15th International Learning Analytics and Knowledge Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W44514345","https://openalex.org/W571814998","https://openalex.org/W1978710835","https://openalex.org/W1988644426","https://openalex.org/W1990572457","https://openalex.org/W2028878459","https://openalex.org/W2087041628","https://openalex.org/W2202037140","https://openalex.org/W2324217701","https://openalex.org/W2775105814","https://openalex.org/W2795530988","https://openalex.org/W2796792862","https://openalex.org/W2896455170","https://openalex.org/W4200275892","https://openalex.org/W4206015129","https://openalex.org/W4234384353","https://openalex.org/W4281793922","https://openalex.org/W4298306681","https://openalex.org/W4300875424","https://openalex.org/W4381144969","https://openalex.org/W4381145042","https://openalex.org/W4392681908"],"related_works":["https://openalex.org/W768569191","https://openalex.org/W1535358919","https://openalex.org/W4241226487","https://openalex.org/W2370302780","https://openalex.org/W4241924370","https://openalex.org/W1998175889","https://openalex.org/W2039867343","https://openalex.org/W3174101689","https://openalex.org/W2168747096","https://openalex.org/W52703274"],"abstract_inverted_index":{"Learning":[0],"is":[1,34,108,150],"a":[2,70,92,113,126,145,151],"complex":[3,12],"process":[4,134],"that":[5],"occurs":[6],"over":[7],"time.":[8],"To":[9],"represent":[10],"this":[11],"process,":[13],"interests":[14],"has":[15],"been":[16],"rising":[17],"in":[18,83],"conceptualizing":[19],"and":[20,43,62,72,96,142,158],"integrating":[21],"temporality":[22],"into":[23,46],"model":[24,33,60,84],"constructions.":[25],"However,":[26],"the":[27,133],"construction":[28],"of":[29,52,59,64,129,135,147],"an":[30,101],"event-based":[31,160],"temporal":[32,48,98,156,161],"challenging.":[35],"Specifically,":[36],"researchers":[37],"struggle":[38],"with":[39,116],"translating":[40],"qualitative":[41,93,118],"heuristics":[42],"theoretical":[44],"hypotheses":[45],"quantifiable":[47],"parameters.":[49],"Existing":[50],"methods":[51],"parameter":[53],"derivation":[54],"also":[55],"suffer":[56],"from":[57],"issues":[58],"transparency":[61],"oversimplification":[63],"learning":[65,122],"contexts.":[66],"Thus,":[67],"we":[68,131],"proposed":[69],"conceptual":[71],"methodological":[73],"framework,":[74],"Qualitative":[75],"Parameter":[76],"Triangulation":[77],"(QPT),":[78],"to":[79,109],"center":[80],"human":[81,88],"interpretation":[82],"construction.":[85],"Based":[86],"on":[87],"interpretations,":[89],"QPT":[90,149],"constructs":[91],"loss":[94],"function":[95],"derives":[97],"parameters":[99,157],"using":[100],"automatical":[102],"optimization":[103],"algorithm.":[104],"The":[105],"final":[106],"step":[107],"check":[110],"consistency":[111],"between":[112],"global":[114],"representation":[115],"local":[117],"evidence":[119],"given":[120],"specific":[121],"moments.":[123],"By":[124],"presenting":[125],"worked":[127],"example":[128],"QPT,":[130],"demonstrated":[132],"maintaining":[136],"pairwise":[137],"alignments":[138],"across":[139],"interpretation,":[140],"systematization,":[141],"approxi-gation.":[143],"As":[144],"proof":[146],"concept,":[148],"feasible":[152],"framework":[153],"for":[154],"determining":[155],"constructing":[159],"models.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2025-10-10T00:00:00"}
