{"id":"https://openalex.org/W2950414942","doi":"https://doi.org/10.1145/3412347","title":"How Effective Can Simple Ordinal Peer Grading Be?","display_name":"How Effective Can Simple Ordinal Peer Grading Be?","publication_year":2020,"publication_date":"2020-08-31","ids":{"openalex":"https://openalex.org/W2950414942","doi":"https://doi.org/10.1145/3412347","mag":"2950414942"},"language":"en","primary_location":{"id":"doi:10.1145/3412347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412347","pdf_url":null,"source":{"id":"https://openalex.org/S4210173995","display_name":"ACM Transactions on Economics and Computation","issn_l":"2167-8375","issn":["2167-8375","2167-8383"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Economics and Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046035189","display_name":"Ioannis Caragiannis","orcid":"https://orcid.org/0000-0002-4918-7131"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Ioannis Caragiannis","raw_affiliation_strings":["University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026671559","display_name":"George A. Krimpas","orcid":"https://orcid.org/0009-0007-0008-547X"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"George A. Krimpas","raw_affiliation_strings":["University of Patras, Greece"],"affiliations":[{"raw_affiliation_string":"University of Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090907162","display_name":"Alexandros A. Voudouris","orcid":"https://orcid.org/0000-0003-1105-3856"},"institutions":[{"id":"https://openalex.org/I110002522","display_name":"University of Essex","ror":"https://ror.org/02nkf1q06","country_code":"GB","type":"education","lineage":["https://openalex.org/I110002522"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alexandros A. Voudouris","raw_affiliation_strings":["University of Essex, UK"],"affiliations":[{"raw_affiliation_string":"University of Essex, UK","institution_ids":["https://openalex.org/I110002522"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046035189"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.66674236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":"3","first_page":"1","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9898999929428101,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9898999929428101,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9314000010490417,"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":0.6506209373474121},{"id":"https://openalex.org/keywords/grading","display_name":"Grading (engineering)","score":0.6409653425216675},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40476199984550476},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3985399603843689},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36997485160827637},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34295976161956787}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6506209373474121},{"id":"https://openalex.org/C2777286243","wikidata":"https://www.wikidata.org/wiki/Q5591926","display_name":"Grading (engineering)","level":2,"score":0.6409653425216675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40476199984550476},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3985399603843689},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36997485160827637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34295976161956787},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3412347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412347","pdf_url":null,"source":{"id":"https://openalex.org/S4210173995","display_name":"ACM Transactions on Economics and Computation","issn_l":"2167-8375","issn":["2167-8375","2167-8383"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Economics and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W9921517","https://openalex.org/W1129480147","https://openalex.org/W1181125918","https://openalex.org/W1576809162","https://openalex.org/W1854214752","https://openalex.org/W1986978101","https://openalex.org/W2006437246","https://openalex.org/W2012215691","https://openalex.org/W2051834357","https://openalex.org/W2060990051","https://openalex.org/W2063445365","https://openalex.org/W2067602930","https://openalex.org/W2088700588","https://openalex.org/W2096426146","https://openalex.org/W2103868989","https://openalex.org/W2105089228","https://openalex.org/W2114523181","https://openalex.org/W2115073724","https://openalex.org/W2138170247","https://openalex.org/W2140897975","https://openalex.org/W2151970144","https://openalex.org/W2166164009","https://openalex.org/W2221311665","https://openalex.org/W2241862190","https://openalex.org/W2339921488","https://openalex.org/W2340985688","https://openalex.org/W2466887399","https://openalex.org/W2560674852","https://openalex.org/W2560931883","https://openalex.org/W2605961645","https://openalex.org/W2607666848","https://openalex.org/W2608239929","https://openalex.org/W2612288690","https://openalex.org/W2913028927","https://openalex.org/W2950051380","https://openalex.org/W2954631080","https://openalex.org/W2962914180","https://openalex.org/W2963112694","https://openalex.org/W2963433558","https://openalex.org/W2963752051","https://openalex.org/W2963755303","https://openalex.org/W3006452435","https://openalex.org/W4238758628","https://openalex.org/W4300616132","https://openalex.org/W4389615664"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Ordinal":[0],"peer":[1],"grading":[2,30,105,120,212,239],"has":[3],"been":[4,245],"proposed":[5],"as":[6,36,171],"a":[7,69,78,93,114,127,146,167],"simple":[8,82],"and":[9,91,192,231],"scalable":[10],"solution":[11],"for":[12,96],"computing":[13],"reliable":[14],"information":[15,102,210],"about":[16,103,211,238],"student":[17,45,125,128],"performance":[18,149,202],"in":[19,199,224,232,251],"massive":[20],"open":[21],"online":[22],"courses.":[23],"The":[24],"idea":[25],"is":[26,46,109,173,221],"to":[27,32,48,135,145,160,175,195],"outsource":[28],"the":[29,33,39,65,104,119,123,130,137,153,157,161,201,218,225,252],"task":[31],"students":[34,108,179,242],"themselves":[35],"follows.":[37],"After":[38],"end":[40],"of":[41,51,54,81,107,113,122,148,203,217,227,241,254],"an":[42,215],"exam,":[43],"each":[44],"asked":[47],"rank\u2014in":[49],"terms":[50,112],"quality\u2014a":[52],"bundle":[53],"exam":[55],"papers":[56],"by":[57,156],"fellow":[58],"students.":[59,75],"An":[60],"aggregation":[61,83,89,158,204],"rule":[62,139,159,169],"then":[63],"combines":[64],"individual":[66],"rankings":[67],"into":[68],"global":[70],"one":[71],"that":[72,117,151,188,243],"contains":[73],"all":[74],"We":[76],"define":[77],"broad":[79],"class":[80,142],"rules,":[84,90],"which":[85],"we":[86,184,235],"call":[87],"type-ordering":[88],"present":[92,185],"theoretical":[94,229],"framework":[95,131,230],"assessing":[97],"their":[98],"effectiveness.":[99],"When":[100],"statistical":[101],"behaviour":[106,121,213,240],"available":[110],"(in":[111],"noise":[115,219],"matrix":[116],"characterizes":[118],"average":[124],"from":[126,140,247],"population),":[129],"can":[132],"be":[133,176,196],"used":[134],"compute":[136],"optimal":[138,177],"this":[141],"with":[143],"respect":[144],"series":[147],"objectives":[150],"compare":[152],"ranking":[154],"returned":[155],"underlying":[162],"ground-truth":[163],"ranking.":[164],"For":[165],"example,":[166],"natural":[168],"known":[170],"Borda":[172],"proved":[174],"when":[178,207],"grade":[180],"correctly.":[181],"In":[182],"addition,":[183],"extensive":[186],"simulations":[187],"validate":[189],"our":[190,228,233],"theory":[191],"prove":[193],"it":[194],"extremely":[197],"accurate":[198],"predicting":[200],"rules":[205],"even":[206],"only":[208],"rough":[209],"(i.e.,":[214],"approximation":[216],"matrix)":[220],"available.":[222],"Both":[223],"application":[226],"simulations,":[234],"exploit":[236],"data":[237],"have":[244],"extracted":[246],"two":[248],"field":[249],"experiments":[250],"University":[253],"Patras.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
