From Prophetic Tradition to Digital Learning: Transforming Classical Knowledge Verification Methods into Contemporary AI Ethics for Sustainable Education

Digital learning transformation has accelerated the integration of artificial intelligence in educational systems, yet algorithmic bias in AI-powered educational technologies disproportionately affects marginalized communities and undermines sustainable education goals. Current bias mitigation strategies, predominantly rooted in Western epistemological frameworks, inadequately address the need for culturally-responsive approaches to educational AI ethics, particularly for the global Muslim educational community comprising 25% of the world's population. This study develops a comprehensive epistemological framework that transforms classical Islamic knowledge verification methodologies—specifically isnād (chain of transmission), jarḥ wa ta'dīl (source criticism), and mutawātir (cross-validation)—into practical guidelines for bias detection and mitigation in educational AI systems.

Through systematic literature review and conceptual synthesis, this research bridges prophetic traditions with contemporary educational technology ethics by operationalizing Islamic moral principles including justice ('adl), excellence (iḥsān), and public interest (maṣlaḥa) as ethical guidelines for sustainable educational AI deployment. The study transforms traditional hadith verification methods into modern data provenance tracking, source credibility assessment, and multi-source validation protocols specifically designed for educational contexts including adaptive learning systems, automated assessment platforms, and educational recommendation algorithms.

Findings demonstrate that prophetic epistemological frameworks provide robust foundations for developing critical awareness of algorithmic bias in educational settings, offering culturally-sensitive tools for data evaluation, enhanced methodologies for educational AI validation, and systematic approaches to ensuring equity in digital learning transformation. The research contributes a three-phase practical framework for educators and educational technologists: bias identification through prophetic verification principles, evaluation using Islamic epistemological criteria, and mitigation based on Islamic ethical values.