Reclaiming the Translator’s Agency in AI-Assisted Training: An Approach Based on Self-Regulated Learning

This study investigated the impact of integrating self-regulated learning strategies into AI-based translation training. Twenty-one undergraduate translation students were divided into control and experimental groups. While both groups used ChatGPT for doing translation tasks, only the experimental group received instruction based on SRL principles. Targeted weekly feedback also played a critical role in guiding students’ learning processes. Translation performance was assessed through pre and posttests using Waddington’s model, and SRL development was measured using the MSLQ and weekly reflective journals. The results showed significant improvement in the experimental group's translation quality and self-regulatory behaviors. Thematic analysis of journals indicated a shift from dependence on AI to empowered decision-making. These findings suggest that SRL-based instruction, when paired with structured feedback, enhances not only students’ interaction with AI tools but also their autonomy, critical thinking and engagement. The study highlights the value of pedagogically grounded use of AI in translator education.

کلیدواژه ها:

Translator’s agency ، AI ، translator training ، Self-regulated learning ، Feedback