Strategic Principal Leadership in Data-Driven and Value-Based School Planning: A Case Study from Indonesian Primary Education - Nurbani, Destisari; Nurdin, Diding; Dikdik, Asep (Faculty of Tarbiyah and Education, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta, 2025)
Purpose – This study investigates the leadership strategies of school principals in implementing data-driven planning integrated with religious values, addressing a critical gap in educational leadership literature. While the use of data in school planning is widely discussed, its alignment with spiritual and local cultural values remains underexplored, particularly within multicultural primary schools in Indonesia. Design/methods/approach – A qualitative single case study was conducted at SDN Buahkapas, West Java, using an interpretive epistemology. Data collection included in-depth interviews, non-participant observations, and document analysis (e.g., Education Report Card, annual work plan). Thematic analysis, supported by NVivo software, was employed to identify, code, and visualize recurring patterns across data sources and informants. Findings – The principal demonstrated strategic leadership through comprehensive data analysis (aided by NVivo-based word cloud and project mapping), teacher collaboration, and the integration of religious values into the school’s vision—“SAKTI” (Sehat, Agamis, Kreatif, Berteknologi, dan Inspiratif). Key themes included data-driven planning (19 references), classifying priorities (17), and collaboration (13). Challenges such as limited teacher data literacy and financial constraints were addressed through reflective evaluations, capacity-building efforts, and external resource mobilization. Research implications – Findings highlight the importance of strengthening principals’ data literacy and capacity to embed spiritual values in school planning. Integrated training and teacher empowerment in data interpretation are essential to ensure contextually responsive and evidence-based school improvement. While findings are contextually rich, their generalizability is limited due to the single-case design.