Generative Artificial Intelligence Ethics in Language Education: Evidence from a Systematic Review and Thematic Synthesis of Research in Türkiye (2022–2026)

Generative artificial intelligence has entered language education faster than frameworks and policy guidance for teacher educators and teachers. This focused systematic review synthesizes empirical evidence on the ethical dimensions of generative artificial intelligence use in language education in Türkiye. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a systematic literature review was carried out, and nine studies obtained from the Web of Science and Scopus databases were included in the analysis. Thematic synthesis revealed four themes: (1) contested academic integrity, authorship, and originality; (2) overreliance and erosion of human cognitive and authorial control; (3) ethics–competence gap in artificial intelligence literacy; and (4) responsible use as mediated and institutionally governed practice. The results showed that ethical competence appeared comparatively weaker than other artificial intelligence–related competencies as ethical awareness ranked lower than both artificial intelligence literacy and pedagogical integration among teachers, and plagiarism attitudes were not significantly associated with artificial intelligence literacy. Within the four artificial intelligence literacy dimensions, ethics was the weakest predictor of teachers’ technology acceptance, although it remained statistically significant. Teachers embraced artificial intelligence as a supplementary tool, provided that human authorship and judgment were not compromised, and those who used artificial intelligence selectively retained stronger authorial control. They positioned artificial intelligence as a conditional participant on teacher-defined terms, while institutional support, infrastructure, and policy alignment were linked to ethical practice alongside individual competence. The reviewed literature mostly included perceptual, self-reported, and cross-sectional studies and lacked interventions, underscoring the need for longitudinal, experimental, and intervention research. Cite this article as: Işıklıgil, N. C. C., & Gülbak, G. M. (2026). Generative artificial intelligence ethics in language education: evidence from a systematic review and thematic synthesis of research in Türkiye (2022–2026). HAYEF: Journal of Education, 23, 0097, doi: 10.5152/hayef.2026.26097.