{"id":"https://openalex.org/W4409427481","doi":"https://doi.org/10.1109/zcict63770.2024.10958460","title":"Finding the Best Fit; Comparative Analysis of Supervised Learning Models for Student Feedback Classification","display_name":"Finding the Best Fit; Comparative Analysis of Supervised Learning Models for Student Feedback Classification","publication_year":2024,"publication_date":"2024-11-28","ids":{"openalex":"https://openalex.org/W4409427481","doi":"https://doi.org/10.1109/zcict63770.2024.10958460"},"language":"en","primary_location":{"id":"doi:10.1109/zcict63770.2024.10958460","doi":"https://doi.org/10.1109/zcict63770.2024.10958460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/zcict63770.2024.10958460","pdf_url":null,"source":{"id":"https://openalex.org/S7407087239","display_name":"Zimbabwe Conference of Information and Communication Technologies (ZCICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 3rd Zimbabwe Conference of Information and Communication Technologies (ZCICT)","raw_type":"proceedings-article"},"volume":null,"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/A5117141110","display_name":"Takudzwa Delpha Mangachena","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210101443","display_name":"Arrupe Jesuit University","ror":"https://ror.org/00pffe521","country_code":"ZW","type":"education","lineage":["https://openalex.org/I4210101443"]}],"countries":["ZW"],"is_corresponding":false,"raw_author_name":"Takudzwa Delpha Mangachena","raw_affiliation_strings":["School of Engineering and ICT, Arrupe Jesuit University,Harare,Zimbabwe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and ICT, Arrupe Jesuit University,Harare,Zimbabwe","institution_ids":["https://openalex.org/I4210101443"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5117141111","display_name":"Eva Tsitsi Chigodo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210101443","display_name":"Arrupe Jesuit University","ror":"https://ror.org/00pffe521","country_code":"ZW","type":"education","lineage":["https://openalex.org/I4210101443"]}],"countries":["ZW"],"is_corresponding":false,"raw_author_name":"Eva Tsitsi Chigodo","raw_affiliation_strings":["School of Engineering and ICT, Arrupe Jesuit University,Harare,Zimbabwe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and ICT, Arrupe Jesuit University,Harare,Zimbabwe","institution_ids":["https://openalex.org/I4210101443"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210101443"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31385083,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9961000084877014,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9961000084877014,"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":0.002300000051036477,"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/T12260","display_name":"Educational Technology and Pedagogy","score":0.000699999975040555,"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/course-evaluation","display_name":"course evaluation","score":0.9229999780654907},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"sentiment analysis","score":0.9539999961853027},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8130000233650208},{"id":"https://openalex.org/keywords/multinomial-naive-bayes","display_name":"multinomial naive Bayes","score":0.8920000195503235},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9769999980926514},{"id":"https://openalex.org/keywords/bert","display_name":"BERT","score":0.9869999885559082},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9070000052452087},{"id":"https://openalex.org/keywords/course-quality","display_name":"course quality","score":0.5789999961853027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6672459244728088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5510639548301697},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4991164207458496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/zcict63770.2024.10958460","doi":"https://doi.org/10.1109/zcict63770.2024.10958460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/zcict63770.2024.10958460","pdf_url":null,"source":{"id":"https://openalex.org/S7407087239","display_name":"Zimbabwe Conference of Information and Communication Technologies (ZCICT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 3rd Zimbabwe Conference of Information and Communication Technologies (ZCICT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality education","score":0.9235000014305115}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0],"study":[1],"developed":[2],"a":[3,28,32,99,110,130],"machine":[4,63],"learning-based":[5],"system":[6,108,164],"to":[7,18,56,86,171],"analyze":[8],"student":[9,135],"feedback":[10,21,38],"on":[11,161],"the":[12,20,60,88,143,163],"quality":[13],"of":[14,134],"university":[15,34,155],"courses,":[16],"aiming":[17],"streamline":[19],"process":[22],"and":[23,48,58,72,82,119,125,168],"enhance":[24],"instructional":[25],"delivery.":[26],"Using":[27],"dataset":[29,144],"collected":[30],"from":[31],"Zimbabwean":[33],"Political":[35],"Philosophy":[36],"students,":[37],"was":[39,93],"gathered":[40],"through":[41,50],"Google":[42],"Forms,":[43],"formatted":[44],"as":[45],"CSV":[46],"files,":[47],"processed":[49],"Natural":[51],"Language":[52],"Processing":[53],"(NLP)":[54],"techniques":[55],"clean":[57],"tokenize":[59],"text.":[61],"Three":[62],"learning":[64,78,139],"models\u2014Support":[65],"Vector":[66],"Machine":[67],"(SVM),":[68],"Logistic":[69],"Regression":[70],"(LR),":[71],"Multinomial":[73],"Naive":[74],"Bayes":[75],"(MNB)\u2014alongside":[76],"deep":[77,138],"models":[79,140],"like":[80],"BERT":[81],"CNN,":[83],"were":[84],"tested":[85],"identify":[87],"most":[89],"effective":[90],"classifier.":[91],"SVM":[92,146],"selected":[94],"after":[95],"hyperparameter":[96],"tuning,":[97],"achieving":[98],"reliable":[100],"80%":[101],"accuracy":[102],"in":[103,154],"sentiment":[104,123],"classification.":[105],"The":[106],"final":[107],"generates":[109],"PDF-based":[111],"Course":[112],"Evaluation":[113],"Summary":[114],"Report":[115],"that":[116],"presents":[117],"positive":[118],"negative":[120],"feedback,":[121],"key":[122],"insights,":[124],"graphical":[126],"summaries,":[127],"offering":[128],"instructors":[129],"clear,":[131],"actionable":[132],"overview":[133],"perspectives.":[136],"While":[137],"struggled":[141],"with":[142,165],"size,":[145],"proved":[147],"optimal":[148],"for":[149],"small":[150],"data":[151],"contexts":[152],"typical":[153],"settings.":[156],"Future":[157],"work":[158],"will":[159],"focus":[160],"scaling":[162],"advanced":[166],"NLP":[167],"larger":[169],"datasets":[170],"broaden":[172],"its":[173],"applicability.":[174]},"counts_by_year":[],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2025-10-10T00:00:00"}
