Unpacking Key Systems Towards a Sustainable Education Ecosystem

Predicting the sustainability of national educational systems presents a complex, multifaceted issue due to the intricate connections between education and wider societal, economic, healthcare, and technological sectors. Current educational models tend to be rigid, narrow in focus, and insufficiently responsive to these changing external factors. This research seeks to fill this void by framing education as an ecosystem and creating a methodological framework that merges systems thinking with sophisticated data-driven methods. The study’s aim is to outline, quantify, and analyze the relationships among education-related subsystems to guide the creation of an adaptive, sustainability-focused educational ecosystem. A mixed-methods approach was utilized, incorporating qualitative coding, system mapping, and natural language processing techniques (specifically Word2Vec) to uncover relational patterns within a structured literature set. These findings were integrated with quantitative metrics to assess subsystem efficacy and pinpoint leverage points. The investigation centers on five primary systems in the education ecosystem: Business, Economic, Government, Healthcare, and Sustainability. The Word2Vec analysis identified significant conceptual relationships between these systems, while the quantitative evaluation indicated strong performance across curriculum, policy, and healthcare metrics. Conversely, inclusivity and accreditation displayed weaker outcomes, indicating areas that need focused improvement. The results highlight the benefits of merging systems thinking with NLP-driven relational analysis as a methodological innovation in education research. The study offers evidence-based recommendations for prioritizing factors that can boost system efficacy and create beneficial cross-system ripple effects, aiding in the advancement of adaptive and sustainable educational ecosystems.