{"id":"https://openalex.org/W4306317419","doi":"https://doi.org/10.1145/3511808.3557108","title":"Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning","display_name":"Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317419","doi":"https://doi.org/10.1145/3511808.3557108"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557108","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557108","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557108","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557108","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000769601","display_name":"Yun-Wei Chu","orcid":"https://orcid.org/0000-0003-4443-070X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun-Wei Chu","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059750214","display_name":"Seyyedali Hosseinalipour","orcid":"https://orcid.org/0000-0003-4266-4000"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyyedali Hosseinalipour","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090537862","display_name":"Elizabeth Tenorio","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elizabeth Tenorio","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112754293","display_name":"Laura Cruz","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Laura Cruz","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049462632","display_name":"Kerrie Douglas","orcid":"https://orcid.org/0000-0002-2693-5272"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kerrie Douglas","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063813962","display_name":"Andrew Lan","orcid":"https://orcid.org/0000-0002-8475-6600"},"institutions":[{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Lan","raw_affiliation_strings":["University of Massachusetts Amherst, Amherst, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, Amherst, MA, USA","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020399355","display_name":"Christopher G. Brinton","orcid":"https://orcid.org/0000-0003-2771-3521"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Brinton","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3033","last_page":"3042"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9987000226974487,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9984999895095825,"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/T12676","display_name":"Machine Learning and ELM","score":0.9771000146865845,"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/computer-science","display_name":"Computer science","score":0.762454628944397},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.7397319078445435},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.736197829246521},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6137654781341553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5621013641357422},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.555168628692627},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.346218079328537},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.17885833978652954}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.762454628944397},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.7397319078445435},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.736197829246521},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6137654781341553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5621013641357422},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.555168628692627},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.346218079328537},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.17885833978652954},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557108","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557108","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557108","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3511808.3557108","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3511808.3557108","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3511808.3557108","source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G2473949271","display_name":null,"funder_award_id":"CNS-2146171","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2657468873","display_name":"Collaborative Research: Student Affect Detection and Intervention with Teachers in the Loop","funder_award_id":"1917713","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G474493333","display_name":"CAREER: From Federated to Fog Learning: Expanding the Frontier of Model Training in Heterogeneous Networks","funder_award_id":"2146171","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6621861463","display_name":null,"funder_award_id":"CNS-2146171 ; IIS-1917713","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320314598","display_name":"Charles Koch Foundation","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306317419.pdf","grobid_xml":"https://content.openalex.org/works/W4306317419.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1978380814","https://openalex.org/W2097731551","https://openalex.org/W2104094955","https://openalex.org/W2322861433","https://openalex.org/W2412453891","https://openalex.org/W2605961645","https://openalex.org/W2699539148","https://openalex.org/W2797587201","https://openalex.org/W2894135568","https://openalex.org/W2896763200","https://openalex.org/W2914769558","https://openalex.org/W2915273119","https://openalex.org/W2963392941","https://openalex.org/W3032407425","https://openalex.org/W3096575661","https://openalex.org/W3112044954","https://openalex.org/W3151746723","https://openalex.org/W3155152998","https://openalex.org/W4290961008"],"related_works":["https://openalex.org/W2108595774","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W87991986","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116"],"abstract_inverted_index":{"Traditional":[0],"learning-based":[1],"approaches":[2],"to":[3,8,13,108],"student":[4,10,27,61,72,87,104,146,151,162],"modeling":[5,147],"generalize":[6],"poorly":[7],"underrepresented":[9],"groups":[11,41],"due":[12],"biases":[14],"in":[15,51,54,122,149],"data":[16],"availability.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21,89,136],"propose":[22],"a":[23,66,94,117],"methodology":[24,98,168],"for":[25,59,79,154],"predicting":[26,150],"performance":[28],"from":[29,65,133],"their":[30],"online":[31,134],"learning":[32,152],"activities":[33],"that":[34,77,99,138,165],"optimizes":[35],"inference":[36,181],"accuracy":[37],"over":[38,144],"different":[39,171,175],"demographic":[40],"such":[42],"as":[43],"race":[44],"and":[45,111,115],"gender.":[46],"Building":[47],"upon":[48],"recent":[49],"foundations":[50],"federated":[52],"learning,":[53],"our":[55,91,139,166],"approach,":[56],"personalized":[57],"models":[58,73],"individual":[60],"subgroups":[62],"are":[63],"derived":[64],"global":[67],"model":[68,124],"aggregated":[69],"across":[70],"all":[71,155],"via":[74],"meta-gradient":[75],"updates":[76],"account":[78],"subgroup":[80],"heterogeneity.":[81],"To":[82],"learn":[83],"better":[84],"representations":[85],"of":[86,103,159],"activity,":[88],"augment":[90],"approach":[92,140],"with":[93,178,184],"self-supervised":[95],"behavioral":[96],"pretraining":[97],"leverages":[100],"multiple":[101],"modalities":[102],"behavior":[105],"(e.g.,":[106],"visits":[107],"lecture":[109],"videos":[110],"participation":[112],"on":[113,129],"forums),":[114],"include":[116],"neural":[118],"network":[119],"attention":[120],"mechanism":[121],"the":[123,160,185],"aggregation":[125],"stage.":[126],"Through":[127],"experiments":[128],"three":[130],"real-world":[131],"datasets":[132],"courses,":[135],"demonstrate":[137],"obtains":[141],"substantial":[142],"improvements":[143],"existing":[145],"baselines":[148],"outcomes":[153],"subgroups.":[156],"Visual":[157],"analysis":[158],"resulting":[161],"embeddings":[163],"confirm":[164],"personalization":[167],"indeed":[169],"identifies":[170],"activity":[172],"patterns":[173],"within":[174],"subgroups,":[176],"consistent":[177],"its":[179],"stronger":[180],"ability":[182],"compared":[183],"baselines.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
