Leveraging machine learning approaches for precision education

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dc.contributor.authorAkıntola, Favour Oreoluwa
dc.contributor.authorParuğ Duru, İzzet
dc.date.accessioned2025-09-03T08:52:46Z
dc.date.available2025-09-03T08:52:46Z
dc.date.issued2025
dc.departmentMeslek Yüksekokulu, Gedik Meslek Yüksekokulu, Tıbbi Görüntüleme Teknikleri Programı
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, İşletme Ana Bilim Dalı
dc.description.abstractThis study explores the transformative impact of machine learning (ML) in precision education by analyzing AI-driven adaptive learning strategies and their influence on student engagement and educator efficiency. Utilizing simulated survey data generated through ChatGPT from 400 participants across diverse educational backgrounds, the study employs supervised learning techniques to develop predictive models for student success. Results indicate a strong correlation between AI-based interventions and improved academic performance (Cronbach’s alpha: 0.996, Predictive Accuracy: 85%). Ethical considerations, including data privacy, fairness, and interpretability of AI models, are addressed to ensure responsible implementation. The study provides actionable insights for policymakers and educators to leverage AI tools for scalable, sustainable educational improvements.
The findings highlight the potential of early identification and tailored interventions to significantly enhance both student performance and educator efficiency. The article also addresses the ethical challenges and implications of using AI-driven tools in education, emphasizing responsible data management and bias prevention. Machine learning plays a central role in precision education by enabling personalized learning experiences [1], [3].
The study offers actionable insights for educators and policymakers seeking to implement scalable AI-driven educational improvements.
dc.identifier.endpage43
dc.identifier.issn2791-8335
dc.identifier.issue1
dc.identifier.startpage35
dc.identifier.urihttps://dergipark.org.tr/tr/pub/jaida/issue/92818/1641392
dc.identifier.urihttps://hdl.handle.net/11501/2354
dc.identifier.volume5
dc.institutionauthorAkıntola, Favour Oreoluwa
dc.institutionauthorParuğ Duru, İzzet
dc.institutionauthorid0009-0009-0090-2948
dc.institutionauthorid0000-0002-9227-2497
dc.language.isoen
dc.publisherİzmir Katip Çelebi Üniversitesi
dc.relation.ispartofJournal of Artificial Intelligence and Data Science (JAIDA)
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMachine Learning
dc.subjectPrecision Education
dc.subjectAdaptive Learning
dc.subjectPredictive Analytics
dc.subjectEducational Data Analysis.AI Ethics in Education
dc.titleLeveraging machine learning approaches for precision education
dc.typeArticle

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