MACHINE LEARNING FOR ENHANCED CLASSROOM HOMOGENEITY IN PRIMARY EDUCATION

Basit Öğe Kaydı
dc.contributor.authorBulut, Faruk
dc.contributor.authorDonmez, Ilknur
dc.contributor.authorInce, Ibrahim Furkan
dc.contributor.authorPetrov, Pavel
dc.date.accessioned2025-03-26T15:54:26Z
dc.date.available2025-03-26T15:54:26Z
dc.date.issued2024
dc.departmentİstanbul Esenyurt Üniversitesi
dc.description.abstractA homogeneous distribution of students in a class is accepted as a key factor for overall success in primary education. A class of students with similar attributes normally increases academic success. It is also a fact that general academic success might be lower in some classes where students have different intelligence and academic levels. In this study, a class distribution model is proposed by using some data science algorithms over a small number of students’ dataset. With unsupervised and semi supervised learning methods in machine learning and data mining, a group of students is equally distributed to classes, taking into account some criteria. This model divides a group of students into clusters by the considering students’ different qualitative and quantitative characteristics. A draft study is carried out by predicting the effectiveness and efficiency of the presented approaches. In addition, some process elements such as quantitative and qualitative characteristics of a student, data acquisition style, digitalization of attributes, and creating a future prediction are also included in this study. Satisfactory and promising experimental results are received using a set of algorithms over collected datasets for classroom scenarios. As expected, a clear and concrete evaluation between balanced and unbalanced class distributions cannot be performed since these two scenarios for the class distributions cannot be applicable at the same time.
dc.identifier.doi10.55020/iojpe.1390421
dc.identifier.endpage52
dc.identifier.issn1300-915X
dc.identifier.issue1
dc.identifier.startpage33
dc.identifier.trdizinid1230747
dc.identifier.urihttps://doi.org/10.55020/iojpe.1390421
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1230747
dc.identifier.urihttps://hdl.handle.net/20.500.14704/511
dc.identifier.volume13
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofInternational Online Journal of Primary Education
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TR_20250326
dc.subjectEğitim
dc.subjectEğitim Araştırmaları
dc.subjectEğitim
dc.subjectÖzel
dc.titleMACHINE LEARNING FOR ENHANCED CLASSROOM HOMOGENEITY IN PRIMARY EDUCATION
dc.typeArticle

Dosyalar

Koleksiyon

TR-Dizin İndeksli Yayınlar Koleksiyonu