Artificial Intelligence in Critical Media Literacy: Enhancing Bias Detection, News Evaluation, Algo-Rithm Understanding

This study examines the impact of AI-enhanced critical media literacy training on English as a Foreign Language (EFL) learners’ ability to identify implicit bias, evaluate news accuracy, and critically analyze AI-generated digital content. Using a mixed methods design, the study combined quantitative assessments and qualitative interviews to evaluate a six-week interven-tion that integrated instructor-led instruction with AI-based analytical tools. Findings showed significant gains in bias detection and news verification skills, as well as higher learner moti-vation and critical awareness. In contrast, improvement in algorithmic awareness was limited, indicating the need for more targeted instruction in this area. Overall, the results suggest that AI can effectively support the development of critical media literacy in EFL settings. The study also highlights the importance of incorporating AI literacy into language education cur-ricula. Implications for theory, classroom practice, and future research are discussed, particu-larly for preparing learners to navigate increasingly complex digital information environments effectively.

کلیدواژه ها:

AI literacy ، Artificial intelligence ، Digital media education ، Educational Technology ، Media Literacy