Development of an early warning system for higher education institutions by predicting first-year student academic performance

Basit Öğe Kaydı
dc.contributor.authorCirak, Cem Recai
dc.contributor.authorAkilli, Hakan
dc.contributor.authorEkinci, Yeliz
dc.date.accessioned2024-07-18T20:47:30Z
dc.date.available2024-07-18T20:47:30Z
dc.date.issued2024
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description.abstractIn this study, an early warning system predicting first-year undergraduate student academic performance is developed for higher education institutions. The significant factors that affect first-year student success are derived and discussed such that they can be used for policy developments by related bodies. The dataset used in experimental analyses includes 11,698 freshman students' data. The problem is constructed as classification models predicting whether a student will be successful or unsuccessful at the end of the first year. A total of 69 input variables are utilized in the models. Naive Bayes, decision tree and random forest algorithms are compared over model prediction performances. Random forest models outperformed others and reached 90.2% accuracy. Findings show that the models including the fall semester CGPA variable performed dramatically better. Moreover, the student's programme name and university placement exam score are identified as the other most significant variables. A critical discussion based on the findings is provided. The developed model may be used as an early warning system, such that necessary actions can be taken after the second week of the spring semester for students predicted to be unsuccessful to increase their success and prevent attrition.en_US
dc.identifier.doi10.1111/hequ.12539
dc.identifier.issn0951-5224
dc.identifier.issn1468-2273
dc.identifier.scopus2-s2.0-85192380608en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1111/hequ.12539
dc.identifier.urihttps://hdl.handle.net/11411/7824
dc.identifier.wosWOS:001215256900001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofHigher Education Quarterlyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassification Algorithmsen_US
dc.subjectData Miningen_US
dc.subjectMachine Learningen_US
dc.subjectPerformance Evaluationen_US
dc.subjectRandom Foresten_US
dc.subjectStudent Successen_US
dc.subjectSuccessen_US
dc.subjectSchoolen_US
dc.subjectSelectionen_US
dc.subjectClassificationen_US
dc.titleDevelopment of an early warning system for higher education institutions by predicting first-year student academic performanceen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

Web of Science Indexed Publications
Scopus Indexed Publications