Human and AI Preferences in Turkish Subject Realization: Linguistic and Educational Perspectives
Öz
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
Anahtar Kelimeler
Etik Beyan
Kaynakça
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Uygulamalı Dilbilim ve Eğitim Dilbilimi , Dilbilim (Diğer)
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
30 Nisan 2026
Gönderilme Tarihi
17 Aralık 2025
Kabul Tarihi
13 Mart 2026
Yayımlandığı Sayı
Yıl 2026 Cilt: 12 Sayı: 1