{"id":"https://openalex.org/W4367308974","doi":"https://doi.org/10.1109/iceit57125.2023.10107887","title":"A Study of Academic Achievement Attribution Analysis Based on Explainable Machine Learning Techniques","display_name":"A Study of Academic Achievement Attribution Analysis Based on Explainable Machine Learning Techniques","publication_year":2023,"publication_date":"2023-03-16","ids":{"openalex":"https://openalex.org/W4367308974","doi":"https://doi.org/10.1109/iceit57125.2023.10107887"},"language":"en","primary_location":{"id":"doi:10.1109/iceit57125.2023.10107887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceit57125.2023.10107887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Educational and Information Technology (ICEIT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100428606","display_name":"Tan Li","orcid":"https://orcid.org/0000-0001-6129-4792"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Li","raw_affiliation_strings":["Beijing Normal University,School of Educational Technology,Beijing,China","School of Educational Technology, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Educational Technology,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"School of Educational Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089057686","display_name":"Weiyi Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiyi Ren","raw_affiliation_strings":["Beijing Normal University,School of Educational Technology,Beijing,China","School of Educational Technology, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Educational Technology,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"School of Educational Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101191876","display_name":"Zhiwen Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Xia","raw_affiliation_strings":["Beijing Normal University,School of Educational Technology,Beijing,China","School of Educational Technology, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Educational Technology,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"School of Educational Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076973592","display_name":"Fati Wu","orcid":"https://orcid.org/0000-0002-6137-7886"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fati Wu","raw_affiliation_strings":["Beijing Normal University,School of Educational Technology,Beijing,China","School of Educational Technology, Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University,School of Educational Technology,Beijing,China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"School of Educational Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.9862,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75969597,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"114","last_page":"119"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9993000030517578,"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":0.9993000030517578,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9413999915122986,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.923799991607666,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7257332801818848},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.656679093837738},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6352891325950623},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5961966514587402},{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.5567236542701721},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.48798006772994995},{"id":"https://openalex.org/keywords/academic-achievement","display_name":"Academic achievement","score":0.4744473695755005},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.46110421419143677},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4530073404312134},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4312838315963745},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.42526954412460327},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.3488914370536804},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.30870938301086426},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.10776969790458679},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.0990438163280487}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7257332801818848},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656679093837738},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6352891325950623},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5961966514587402},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.5567236542701721},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.48798006772994995},{"id":"https://openalex.org/C2781206393","wikidata":"https://www.wikidata.org/wiki/Q2748419","display_name":"Academic achievement","level":2,"score":0.4744473695755005},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.46110421419143677},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4530073404312134},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4312838315963745},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.42526954412460327},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.3488914370536804},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.30870938301086426},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.10776969790458679},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0990438163280487},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceit57125.2023.10107887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceit57125.2023.10107887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Educational and Information Technology (ICEIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2057028674","https://openalex.org/W2071097428","https://openalex.org/W2089111993","https://openalex.org/W2138962140","https://openalex.org/W2153146225","https://openalex.org/W2910705748","https://openalex.org/W2962862931","https://openalex.org/W3206998513","https://openalex.org/W4241452927","https://openalex.org/W6682601585","https://openalex.org/W6737947904"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W2806259446","https://openalex.org/W2963326959","https://openalex.org/W4247136043","https://openalex.org/W4312407344"],"abstract_inverted_index":{"The":[0,167,193],"research":[1,114],"on":[2,94,120,182],"academic":[3,85,158,183,208],"achievement":[4,209],"prediction":[5,43,134],"and":[6,27,44,60,87,124,141,163,185,210],"attribution":[7,45,122],"is":[8,30,48,170,199],"a":[9,38,116],"frontier":[10],"topic":[11],"in":[12],"the":[13,33,42,52,71,75,81,95,101,127,132,153,161,174,196,203],"field":[14],"of":[15,41,54,74,100,109,178],"artificial":[16,22],"intelligence":[17,23],"education.":[18],"However,":[19],"because":[20],"most":[21],"algorithms":[24],"are":[25],"deep":[26],"non-parametric,":[28],"it":[29],"difficult":[31],"for":[32,51,105],"algorithm":[34,130,135],"itself":[35],"to":[36,69,172,187,201],"give":[37],"credible":[39],"explanation":[40],"results,":[46],"which":[47],"very":[49],"dangerous":[50],"education":[53],"cultivating":[55],"students":[56],"with":[57],"rich":[58],"emotions":[59],"values.":[61],"Explainable":[62],"AI":[63],"technology":[64],"can":[65],"assist":[66],"educational":[67],"researchers":[68,78],"clarify":[70],"decision-making":[72],"process":[73],"algorithm,":[76],"help":[77,186],"accurately":[79],"locate":[80],"key":[82],"factors":[83,154,181,205],"affecting":[84],"achievement,":[86],"formulate":[88,188],"targeted":[89,212],"learning":[90,147,190],"intervention":[91,191],"strategies.":[92],"Based":[93],"open":[96],"source":[97],"data":[98],"set":[99,118],"Advanced":[102],"Innovation":[103],"Center":[104],"Future":[106],"Education":[107],"(AICFE)":[108],"Beijing":[110],"Normal":[111],"University,":[112],"this":[113],"constructs":[115],"feature":[117,137],"based":[119],"Weiner's":[121],"theory,":[123],"finally":[125],"determines":[126],"naive":[128],"Bayes":[129],"as":[131],"best":[133],"through":[136],"selection,":[138],"model":[139,142],"training,":[140],"selection;":[143],"Then,":[144],"using":[145],"machine":[146],"interpretability":[148],"framework":[149],"SHAP,":[150],"we":[151],"explored":[152],"that":[155,206],"affect":[156,207],"students'":[157],"achievements":[159],"from":[160],"group":[162],"individual":[164,197],"levels":[165],"respectively.":[166],"group-level":[168],"exploration":[169,194],"helpful":[171],"reveal":[173],"overall":[175],"impact":[176],"trend":[177],"various":[179],"influencing":[180],"achievements,":[184],"group-oriented":[189],"strategies;":[192],"at":[195],"level":[198],"conducive":[200],"finding":[202],"personalized":[204],"achieving":[211],"intervention.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
