Smart Education Recommendation Framework with Dashboard in the Smart City: Smart Education Context

This doctoral research addresses the critical gap in the lack of standardised, ISO/IEC aligned frameworks for Smart Education Recommendation Framework with Dashboard (SERFD) within Smart Cities. Existing frameworks are analysed for their limitations and enhancements are proposed based on available datasets sourced from the World Bank, Open-Data Initiative, UK Data Science, UNESCO, UN-STAT, WEF, and EU-STAT, alongside in-depth case studies. The research culminates in the development of a novel Smart Education Recommendation Framework with Dashboard that incorporates stakeholder perspectives and aligns with broader Smart City initiatives and standards.

Using data analytics concepts and Open Data-driven evaluations, the framework introduces methodologies to evaluate and optimise educational experiences within Smart City ecosystems. Real-world case studies are analysed to establish clear metrics and thresholds for operational efficiency, promoting transparency and informed decision-making. A user-friendly visualisation dashboard empowers stakeholders to assess the impact of various educational interventions, fostering continuous improvement.

This research makes a significant contribution to the field by proposing globally recognised metrics and thresholds for Smart Education within Smart Cities. These are derived from sources of reliable datasets and real-world case studies, offering valuable recommendations to stakeholders. Potential areas for future research are identified, including refining the framework’s adaptability and exploring the integration of XR and AI-driven personalised learning. The practical implications of this framework offer actionable guidance to policymakers, educators, and administrators seeking to optimise educational experiences and infrastructure within Smart City environments.