Understanding Translation Students' Use of AI-Powered Tools During Text Revision and Their Impact on Cognitive Load

This chapter explores how students' cognitive load changes when using writing assistants, machine translation, and AI chatbots for L2 text revision. By contributing to the ongoing scholarly conversation about how various technologies impact language learners' proofreading and post-editing performance, this study also explores how cognitive load theory applies to L2 academic writing. A convergent parallel design was employed to collect data from 41 translation students at a state university in Turkey. Participants engaged in proofreading and post-editing using Grammarly, DeepL, and ChatGPT. Data collection involved a subjective cognitive load scale and open-ended questions. Results indicated non-significant correlations between cognitive load and text revision performance, as well as between cognitive load and technology usage frequency. Notably, ChatGPT was the most frequently used application on a daily basis. An interesting finding is the significant gender difference in cognitive load during post-editing with DeepL, where female students experienced a higher cognitive load.