Rewriting Bias: Integrating AI for Gender-Fair Language in Teaching and Learning

Abstract

The growing call for inclusive education has highlighted the need to use gender-fair language (GFL) in teaching. As artificial intelligence (AI) continues to advance, it offers new ways to recognize and correct biased language in educational materials. This study explores how AI can help detect and rewrite gender bias in English-language teaching texts. Using a mixed-methods design, the research combined AI-based corpus analysis with classroom application. A collection of English teaching materials was examined using AI tools to find gender-biased words and patterns. These materials were then rewritten following GFL principles and used in classroom lessons with secondary students and teachers. Pre- and post-tests, surveys, and interviews captured how students and teachers responded to the AI-revised materials. The results showed that AI effectively identified and corrected gender bias, reduced the use of exclusive language, and improved students’ awareness of gender representation. Students reported feeling more included and respected, while teachers found AI-generated revisions practical and time-saving. The classrooms using AI-revised materials also showed higher levels of engagement and comprehension. The study demonstrates that integrating AI in rewriting bias fosters a more inclusive and gender-sensitive approach to teaching and learning. Results provide support that AI can serve as a reliable support for educators in promoting fairness, equality, and respect through language. These findings provide useful insights for teachers, curriculum developers, and policymakers aiming to create educational systems that speak the language of inclusion.