MITIGATING COGNITIVE OVER-RELIANCE IN TFL

Abstract

This article explores the growing challenge of cognitive over-reliance on artificial intelligence (AI) in Teaching Foreign Languages (TFL), with a particular focus on academic writing. Although AI tools such as translation systems, paraphrasing platforms, and text generators can support language development and reduce writing anxiety, several researchers argue that excessive dependence on automated output may weaken independent reasoning and cultural awareness. By synthesizing insights from Kolegova and Levina (2024), Crompton et al. (2024), and Dugošija (2024), the discussion highlights a tension between the advantages of AI-assisted learning and its potential risks for academic integrity and critical thinking. In response to these concerns, the article proposes five AI-resistant rubric criteria designed to help teachers evaluate deeper cognitive engagement in TFL writing. These criteria emphasize contextualized argumentation, authorial voice, source evaluation, cognitive flexibility, and original problem-framing. The framework encourages more responsible and reflective AI use, supporting the development of analytical skills in foreign language learners.