Yabancı dilde konuşma becerisinin üretken yapay zekâ ile değerlendirilmesi

Yıl 2025, Sayı: Sosyal Bilimlerde Yapay Zeka: Kuram, Uygulama ve Gelecek Perspektifleri, 169 - 184, 07.12.2025

Oğuz İbrahim Dündar

https://izlik.org/JA58MZ37WA

Öz

Bu hızlı derleme çalışması, üretken yapay zekâ (ÜYZ) destekli araçların yabancı dil öğrenen bireylerin konuşma becerilerinin değerlendirilmesindeki rolünü tematik analiz yöntemiyle incelemektedir. Çalışma kapsamında, alan yazında konuya odaklanan 67 çalışma taranmış; 2018-2025 yılları arasında yayımlanan, ÜYZ araçlarının kullanıldığı ve yabancı dil öğrenenlerle yürütülmüş 7 ampirik araştırma belirlenen ölçütlere göre derinlemesine analiz edilmek üzere seçilmiştir. Veri toplama sürecinde Scopus, Google Scholar, Web of Science ve EBSCO gibi dört büyük akademik veri tabanı kullanılmıştır. Elde edilen bulgular dört ana tema etrafında toplanmaktadır: (1) otomatik geribildirim ve bireyselleştirilmiş değerlendirme (2) dil yeterlilikleri ve öğrenen özerkliği üzerindeki etkiler, (3) yenilikçi teknik yaklaşımlar, (4) sistemsel sınırlılıklar ve etik meseleler. Büyük dil modelleri ve otomatik konuşma tanıma teknolojileri, öğrencilere anlık, detaylı ve hedefe yönelik geribildirim sunarak öğrenme süreçlerini bireyselleştirmekte ve öğretmenlerin ölçme-değerlendirme yükünü önemli ölçüde azaltmaktadır. Ancak bu sistemler, kültürel duyarlılık, duygusal zekâ ve bağlamsal esneklik açısından hâlâ çeşitli sınırlılıklar taşımaktadır. Çalışma, ÜYZ tabanlı değerlendirme uygulamalarının pedagojik hedeflerle uyumlu, etik ve kültürel açıdan duyarlı bir yaklaşımla ele alınmasının gerekliliğini vurgulamaktadır.

Anahtar Kelimeler

Hızlı derleme , Konuşma becerisi , Ölçme-değerlendirme , Üretken yapay zekâ , Yapay zekâ

Evaluating foreign language speaking proficiency using generative artificial intelligence

https://izlik.org/JA58MZ37WA

Öz

This rapid review study explores the role of generative artificial intelligence (GAI)-powered tools in assessing the speaking skills of foreign language learners, employing a thematic analysis approach. A total of 67 studies focused on the topic were initially identified through a literature search. Of these, seven empirical studies, published between 2018 and 2025, involving foreign language learners, and utilizing GAI tools, were selected for in-depth analysis based on defined inclusion criteria. Data collection was carried out using four major academic databases: Scopus, Google Scholar, Web of Science, and EBSCO.
The findings are organized under four main themes: (1) automated feedback and personalized assessment processes, (2) linguistic competence and learner autonomy, (3) innovative technical and pedagogical approaches, and (4) ethical, cultural, and systemic limitations. Large language models and automatic speech recognition technologies provide learners with immediate, detailed, and targeted feedback, thereby personalizing learning and significantly reducing teachers’ assessment workload. However, these systems still face limitations in terms of cultural sensitivity, emotional intelligence, and contextual adaptability. The study emphasizes the importance of adopting GAI-based assessment practices that align with pedagogical goals and are ethically and culturally responsive.

Anahtar Kelimeler

Artificial intelligence , Assessment , Generative artificial intelligence , Rapid review , Speaking proficiency

Kaynakça

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