Scenario Analysis of the Future of Smart Learning and Data Governance in Managerial Systems
Keywords:
Smart learning, data governance, scenario planning, futures studies, thematic analysis, educational managementAbstract
This study aims to identify key themes and develop forward-looking scenarios connecting smart learning and data governance in managerial systems. This qualitative study used a systematic review and thematic analysis approach. Data were gathered by reviewing 12 peer-reviewed articles published between 2018 and 2025, selected through purposive sampling until theoretical saturation was reached. Thematic coding (open, axial, and selective) was performed using NVivo version 14. The study adopted a conceptual scenario-planning framework grounded in future-oriented thinking. Three main themes emerged: “Transformations in Smart Learning,” “Data Governance in Managerial Systems,” and “Foresight and Scenario Planning in Management.” Each theme included several subthemes and open codes, collectively forming a comprehensive framework for future scenario development. The results indicate that future smart learning will be characterized by data-driven personalization, predictive assessments, and interactive environments, while data governance will require transparent, ethical, and adaptive models. Integrating smart learning with robust data governance demands a unified and future-oriented approach. Developing multiple scenarios provides a strategic tool for managing uncertainty and advancing sustainable development in managerial systems. The findings offer a foundation for policy formulation, educational planning, and enhancing data literacy among administrators.
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