Yapay Zekâ ile Sınav Güvenliği: Akademik Literatürdeki Eğilimler Üzerine Bir İnceleme

Abstract

Son yıllarda yapay zekâ temelli uygulamalar, özellikle dijital ortamda gerçekleştirilen sınavlarda güvenliğe ilişkin yeni yaklaşımları beraberinde getirmiştir. Çevrim içi ve uzaktan yürütülen sınavların yaygınlaşmasıyla birlikte sınav güvenliği, geleneksel yüz yüze uygulamaların ötesine geçerek uzaktan sınav güvenliği uygulamaları, otomatik kopya tespit araçları ve akademik dürüstlüğe ilişkin etik tartışmaları içeren daha geniş bir çerçevede ele alınmaya başlanmıştır. Bu çalışmada, Web of Science veri tabanında 2020–2025 yılları arasında yayımlanan 230 akademik çalışma bibliyometrik analiz yöntemiyle incelenmiştir. Alanın genel gelişim yönü ve araştırma yoğunlukları görünür kılmak amacıyla, analiz sürecinde yayınlar yıllara ve dergilere göre dağılım, öne çıkan yazar ve kurumlar, sıkça kullanılan anahtar kelimeler ve uluslararası işbirliği eğilimleri açısından incelenmiştir. Bulgular, 2020 yılı sonrasında yapay zekâ destekli sınav güvenliği konusundaki yayın sayısında belirgin bir artış olduğunu ve özellikle sınav güvenliği uygulamaları, akademik dürüstlük ve kopya tespiti temalarının literatürde öne çıktığını göstermiştir. Elde edilen bulgular, sınav güvenliğine yönelik çalışmaların teknik çözümlerle sınırlı kalmadığını, pedagojik yaklaşımlar, etik sorumluluklar ve kurumsal düzenlemelerle birlikte ele alındığını ortaya koymaktadır.

Keywords

• Bibliyometrik analiz
• Sınav güvenliği
• Yapay zekâ

Exam Security with Artificial Intelligence: A Review of Trends in the Academic Literature

Abstract

In recent years, AI-based applications have brought about new approaches to security, especially in digitally conducted examinations. With the widespread use of online and remote exams, exam security has begun to be addressed within a broader framework that goes beyond traditional face-to-face testing practices to include remote exam security practices, automated cheating detection tools, and ethical debates regarding academic integrity. In this study, 230 academic publications published in the Web of Science database between 2020 and 2025 were analysed using bibliometric analysis. The analysis process involved the evaluation of the publications by year and journal, prominent authors and institutions, recurring keywords, and patterns of international collaboration in order to highlight the general direction of development in the field and the focus of research. The findings indicated a significant increase in the number of publications on AI-assisted exam security since 2020, with themes such as exam security practices, academic integrity, and cheating detection featuring prominently in the literature. The findings also revealed that that efforts to improve exam security are not limited to technical solutions, but also encompass pedagogical approaches, ethical responsibilities, and institutional arrangements.

Keywords

• Artificial intelligence
• bibliometric analysis
• exam security

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