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Journals / Dil Eğitimi ve Araştırmaları Dergisi / 2026 / Cilt: 12 Sayı: 1

Human and AI Preferences in Turkish Subject Realization: Linguistic and Educational Perspectives

Türkçede Özne Dağılımında İnsan ve Yapay Zekâ Tercihleri: Dilbilimsel ve Eğitimsel Bakış Açıları

Oktay Çınar(İstanbul Medeniyet Üniversitesi)0000-0002-9822-7574
Ebru Karayel Çınar(BAHÇEŞEHİR ÜNİVERSİTESİ)0000-0001-9453-3067
Pages
617–635
Publication Date
2026-04-30
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

Keywords: null and overt subjects, syntax-discourse interface, large language models (LMMs), ChatGPT, Turkish

📌 3 Key Takeaways

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Objective & Hypothesis:ABSTRACT: This study investigates whether ChatGPT exhibits human-like sensitivity to the discursive constraints governing the distribution of null and overt subjects in Turkish.
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Key Findings & Data:The study compares acceptability judgments from 27 native speakers with corresponding evaluations produced by ChatGPT.
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Conclusion & Impact:Keywords: null and overt subjects, syntax-discourse interface, large language models (LMMs), ChatGPT, Turkish
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:boş ve açık özneler · sözdizim-söylem arayüzü · büyük dil modelleri

Abstract

ABSTRACT: This study investigates whether ChatGPT exhibits human-like sensitivity to the discursive constraints governing the distribution of null and overt subjects in Turkish. The study compares acceptability judgments from 27 native speakers with corresponding evaluations produced by ChatGPT. Participants and the model evaluated 24 contextualized Turkish sentences representing four conditions: Topic Continuity with null (TC-Null) or overt subjects (TC-Overt), and Contrastive Focus with null (CF-Null) or overt subjects (CF-Overt). The results displayed that TC-Null and CF-Overt sentences were judged highly acceptable, while CF-Null sentences received the lowest ratings, and TC-Overt sentences were moderately acceptable by human participants. ChatGPT closely mirrored these patterns, with negligible-to-small effect size differences in three of the four conditions and a small-to-moderate difference only in the CF-Overt condition. These findings suggest that ChatGPT successfully captures distributional regularities at the syntax–discourse interface, despite known limitations in discourse reasoning. The study concludes by discussing implications for linguistic theory and language pedagogy, highlighting the potential role of large language models (LMMs) as supplementary tools for teaching context-sensitive grammatical features in Turkish. Keywords: null and overt subjects, syntax-discourse interface, large language models (LMMs), ChatGPT, Turkish

Özet

ÖZ: Bu çalışma, ChatGPT’nin Türkçede boş ve açık öznelerin dağılımını belirleyen söylemsel kısıtlamalara insan benzeri bir duyarlılık gösterip göstermediğini incelemektedir. Çalışmada, 27 anadil Türkçe konuşucusunun kabul edilebilirlik yargıları ile ChatGPT tarafından üretilen değerlendirmeler karşılaştırılmıştır. Katılımcılar ve ChatGPT, 4 farklı koşulu temsil eden toplam 24 bağlamlandırılmış Türkçe tümceyi değerlendirmiştir: boş ya da açık özne içeren konu devamı bağlamları ve boş ve açık özne içeren karşıtsal odak bağlamları. Bulgular, boş özne içeren konu sürekliliği bağlamları ile açık özne içeren karşıtsal odak bağlamlarının yüksek düzeyde kabul edilebilir bulunduğunu; boş özne içeren karşıtsal odak bağlamlarının en düşük puanları aldığını ve açık özne içeren konu sürekliliği bağlamlarının ise anadil konuşucuları tarafından orta düzeyde kabul edilebilir olarak değerlendirildiğini göstermektedir. ChatGPT, bu değerlendirme örüntülerini büyük ölçüde yansıtmış; dört bağlamdan üçünde etki büyüklükleri küçük düzeyde kalırken, yalnızca açık özne içeren karşıtsal odak bağlamlarında küçük ile orta düzey arasında bir fark ortaya çıkmıştır. Bu bulgular, ChatGPT’nin söylemsel alana ilişkin akıl yürütmedeki bilinen sınırlılıklarına rağmen, sözdizim ile söylem arasındaki etkileşimde ortaya çıkan dağılımsal düzenlilikleri başarılı bir biçimde yakalayabildiğini göstermektedir. Çalışma son olarak, dilbilim ve dil öğretimi açısından çıkarımları tartışarak, büyük dil modellerinin Türkçede bağlama duyarlı dilbilgisel özelliklerin öğretiminde tamamlayıcı araçlar olarak değerlendirilebileceğine işaret etmektedir. Anahtar sözcükler: boş ve açık özneler, sözdizim-söylem arayüzü, büyük dil modelleri, ChatGPT, Türkçe

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Cite This Article

Çınar, O., Çınar, E. K. (2026). Human and AI Preferences in Turkish Subject Realization: Linguistic and Educational Perspectives. Dil Eğitimi ve Araştırmaları Dergisi, Cilt: 12 Sayı: 1, 617–635. https://doi.org/10.31464/jlere.1843496

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