Yapay Zeka ve Dil Öğrenme Süreçlerinde Kullanımına Genel Bakış

Year 2025, Volume: 5 Issue: 1, 118 - 130, 31.05.2025

Özgür Şimşek

https://doi.org/10.55008/te-ad.1567106

Abstract

Amaç: Bu derlemenin amacı, yapay zekâ uygulamalarının dil edinim süreçlerinde nasıl kullanıldığını incelemek ve bu süreçleri daha etkili hale getiren yapay zekâ destekli uygulama biçimlerinin geliştirilmesine yönelik araştırmaları değerlendirmektir. Literatür taraması ile yapay zekâ teknolojilerinin dil edinim süreçlerine katkıları incelenmiştir. Araştırmalar, yapay zekâ destekli teknolojilerin kişiselleştirilmiş öğrenme, geniş erişim imkânı ve gelişmiş öğrenme sonuçları sunarak dil eğitiminde devrim yaratma potansiyeline sahip olduğunu göstermektedir. Bununla birlikte, mahremiyet, veri güvenliği, algoritmik önyargılar ve kültürel nüanslar gibi etik sorunlar, yapay zekânın dil öğrenimine entegrasyonu sürecinde önemli zorluklar olarak ele alınmalıdır.

Amaçlar ve Yöntem: Bu derleme, içinde yaşadığımız bu yüzyılda hızla gelişen ve kullanım alanı yaygınlaşan yapay zekâ uygulamalarının dil edinim süreçlerinde kullanım alanlarının tanımlanması, dil edinim süreçlerini, daha etkili hale getiren yapay zekâ destekli uygulama biçimlerinin geliştirilmesi konusunda yapılmış araştırmaları incelemiştir. Literatür taraması yoluyla, yapay zekâ uygulamalarının dil edinim süreçlerinde nasıl kullanılabileceği konusundaki mevcut yöntemler ve bu yöntemlerin içeriği değerlendirilmiştir.

Sonuçlar: Araştırmalar, yapay zekânın dil edinimi üzerindeki etkilerine ilişkin yapay zekâ destekli teknolojilerin eğitime önemli katkılarda bulunduğunu ve yeni olanaklar sunduğunu göstermektedir. Yapay zekâ, kişiselleştirilmiş öğrenme deneyimleri, daha geniş erişilebilirlik ve gelişmiş öğrenme sonuçları sunarak dil eğitiminde devrim yaratma potansiyeline sahiptir. Ancak yapay zekânın dil öğrenimine entegrasyonu konusunda bazı zorluklar vardır. Yapay zekâ destekli dil öğrenme sistemlerinin şeffaflık ve adalet değerlerine saygı göstermesini sağlamak için mahremiyet, veri güvenliği ve algoritmik önyargılarla ilgili etik sorunlar dikkatle ele alınmalıdır. Ayrıca, yapay zekâ algoritmalarının lehçe farklılıkları ve kültürel nüanslar gibi zorlukları ele alması için sürekli olarak rafine edilmesi gerekmektedir.

Keywords

Dil Edinimi, Yapay Zeka, Yapay Zeka Destekli Dil Edinimi

An Overview of the Use of Artificial Intelligence in Language Learning Processes

Abstract

Objective: The purpose of this review is to examine how artificial intelligence (AI) applications are used in language acquisition processes and to evaluate research on the development of AI-supported applications that make these processes more effective. Through a literature review, the contributions of AI technologies to language acquisition processes were explored. Research shows that AI-supported technologies have the potential to revolutionize language education by offering personalized learning, broad accessibility, and improved learning outcomes. However, issues such as privacy, data security, algorithmic biases, and cultural nuances must be addressed as significant challenges in the integration of AI into language learning.

Aims and Method: This review analyzed research on the applications of AI in language acquisition, which has rapidly advanced and expanded in usage in this century. It assessed current methods of utilizing AI in language acquisition processes and evaluated the content of these methods through a literature review.

Results: Studies have shown that AI-supported technologies contribute significantly to education and offer new possibilities in language learning. AI has the potential to revolutionize language education by providing personalized learning experiences, broader accessibility, and enhanced learning outcomes. However, the integration of AI into language learning faces challenges. Ethical concerns such as privacy, data security, and algorithmic biases must be carefully addressed to ensure AI-supported language learning systems respect values of transparency and fairness. Additionally, AI algorithms need continuous refinement to tackle challenges like dialectal differences and cultural nuances.

Keywords

Language Acquisition, Artificial Intelligence, AI-Supported Language Acquisition

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