Teacher talent management and AI readiness for educational management effectiveness: A case study Umar Diharja, Isnaeni Machra Winayu, Wahyu Widada
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Teacher talent management and artificial intelligence (AI) readiness are increasingly important for educational management effectiveness, yet empirical studies that examine their relationship within a single institution remain limited. This manuscript presents a case study design for examining how teacher talent management practices at Sekolah Islam Terpadu Mutiara Cendekia relate to staff AI readiness and educational management effectiveness. The study uses a mixed-methods single-case design. Data will be collected through a questionnaire administered to all teachers and education staff, in-depth interviews with selected leaders and senior teachers, document analysis, and non-participant observation. The analysis will combine descriptive quantitative analysis, thematic qualitative analysis, and source triangulation. The study also distinguishes the evidentiary status of the three talent-mapping instruments used by the school: the Culture Fair Intelligence Test, PAPI Kostick, and fingerprint-based dermatoglyphics testing. The design treats CFIT as a psychometrically established measure, PAPI Kostick as an instrument with documented technical support but debated predictive validity, and dermatoglyphics testing as lacking broadly accepted scientific support for measuring aptitude or intelligence. The expected contribution is an evidence-informed governance model that aligns talent placement, responsible AI adoption, and institutional decision-making without treating weakly supported instruments as decisive personnel evidence.
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