Mapping Teacher Competence in AI-Integrated School Education: A Bibliometric Study (2021–2025) - Fadya Asmadina Aulia; Agus Setiawan; Rama Wijaya Abdul Rozak; Nandang Rusmana; Maulia Depriya Kembara (AL-ISHLAH: Jurnal Pendidikan, 2025)
The rapid integration of Artificial Intelligence (AI) into education has redefined teacher competence, requiring not only technical proficiency but also pedagogical adaptability and ethical awareness. However, existing literature lacks a comprehensive synthesis connecting these dimensions within school-based education. This study employed a bibliometric analysis of 288 Scopus-indexed research articles published between 2021 and 2025. Data were retrieved via ScienceDirect and validated through Scopus. VOSviewer was used to conduct keyword co-occurrence analysis, applying full counting and LinLog/modularity clustering to identify dominant themes. Seventy-six high-frequency keywords were grouped into seven thematic clusters: (1) student outcomes and engagement, (2) teacher development and TPACK integration, (3) AI literacy and readiness, (4) pedagogical innovation and AI systems, (5) generative AI tools and trends, (6) curriculum design and early AI education, and (7) emotional intelligence and institutional support. Key frameworks included TPACK, UNESCO's AI Competency Framework, and self-efficacy models such as TAICS. Findings reveal a multidimensional structure connecting cognitive, affective, and institutional aspects of teacher competence. The study highlights the need for holistic teacher education programs that integrate AI literacy, ethical reasoning, emotional resilience, and contextual pedagogy. Implications are discussed for curriculum developers, policymakers, and professional development initiatives, particularly in emerging contexts like Indonesia.