Abstract The United Nations Sustainable Development Goal (SDG) 4—Quality Education—emphasizes inclusive, equitable, and lifelong learning opportunities for all. In line with this global objective, the Programme for International Student Assessment (PISA), administered every three years by the OECD, evaluates the competencies of 15-year-old students across participating education systems. PISA has become a key benchmark for governments, researchers, and educators in evaluating educational quality and policy effectiveness. However, country rankings are shaped not only by classroom instruction but also by broader social, economic, and systemic factors. This paper investigates two broad sets of influences on PISA performance. Structural factors refer to long-term conditions embedded within education systems, including socioeconomic background, funding, teacher qualifications, and curriculum design. Emerging factors, by contrast, are more recent interventions that aim to accelerate learning outcomes—most notably the integration of artificial intelligence (AI) in education and school-based mental health support. By examining both sets of factors together, this study seeks to provide a comprehensive explanation for differences in PISA outcomes across 81 countries. In particular, it highlights how countries with robust economic conditions, effective teacher support, and targeted innovation in AI and mental health perform better. Understanding these dynamics is crucial for identifying best practices, designing effective education policies, and improving learning outcomes, especially in contexts such as the Philippines, where PISA scores remain among the lowest. This study also contributes to filling research gaps by incorporating AI maturity and mental health interventions—two underexplored drivers—into the analysis of global educational outcomes.
Mesias et al. (Mon,) studied this question.