AI as Wasīlah: A Normative–Historical Framework for Responsible Language Teaching in the Generative AI Era

Abstrak

Generative artificial intelligence (AI) has increasingly become a learning intermediary in language education, raising questions not only about pedagogical effectiveness but also about its epistemological role in the production, mediation, and validation of knowledge. This study explores how a normative–historical perspective in Islamic Studies can inform contemporary language teaching and AI-mediated learning. It draws on a conceptual synthesis of three bodies of scholarship: normative–historical approaches in Islamic Studies; AI, epistemic authority, and Islamic education; and generative AI in language teaching and learning. The literature is analyzed thematically through the concepts of source, authority, context, interpretation, mediation, human agency, and verification. The synthesis indicates that these fields have developed substantially but largely in parallel. Normative–historical studies emphasize the relationship between normative sources and historical context; AI scholarship examines changing forms of epistemic authority and human mediation; and language-teaching research focuses primarily on pedagogical functions, learner engagement, feedback, and language-skill development. In response, this study proposes a conceptual framework in which normativity and historicity provide the epistemological foundation, interpretation mediates between text and context, language teaching constitutes the pedagogical domain, and generative AI serves as wasīlah—a technological means for accessing, exploring, practicing, and processing learning resources rather than a normative source or autonomous authority. Human epistemic agency is preserved through critical interpretation, tabayyun, source verification, and pedagogical judgment. This study proposes a normative–historical framework positioning generative AI as wasīlah in language education while maintaining human responsibility for knowledge and educational decisions.