Teachers’ Digital Literacy in Using Generative AI for Islamic Education: Ethics and Pedagogical Competence
Keywords:
digital literacy, generative artificial intelligence, Islamic education, AI ethics, pedagogical competenceAbstract
Generative artificial intelligence (GenAI) offers opportunities to support
instructional planning, learning materials, and information access in Islamic
education, while raising concerns about information accuracy, source verification,
academic integrity, and teacher responsibility. This article examines teachers’ digital
literacy in utilizing GenAI for Islamic education and considers its relationships with
ethical challenges, pedagogical competence, and pedagogical agency. A qualitative
literature review with conceptual analysis was developed from a relevance-oriented
corpus of 32 scholarly articles collected through Google Scholar, Scopus,
ResearchRabbit, and Open Knowledge. The reviewed scholarship addresses both
Islamic educational contexts and broader research on AI literacy, educational ethics,
and teacher competence. The synthesis distinguishes evidence from context-specific
empirical studies from conceptual and literature-based arguments. Across the
literature, responsible GenAI use is associated with critical evaluation of generated
information, ethical awareness, contextual adaptation of teaching materials, and
teachers’ continued responsibility for educational decisions. The analysis also
indicates that AI-specific literacy is relevant to, but not identical with, broader digital
literacy. In Islamic Religious Education, verification of religious explanations and
alignment with educational values are particularly important considerations. The
article proposes a conceptual connection among digital literacy, ethical evaluation,
pedagogical competence, and pedagogical agency, without claiming a tested causal
relationship. GenAI should therefore be approached as an assistive resource rather
than a replacement for teachers’ professional judgment and moral guidance. Further
classroom-based research is needed to examine these relationships empirically.
