Smart Learning Ecosystems: A SWOT Exploration of AI, IoT, and Big Data

In recent years, Artificial Intelligence (AI), the Internet of Things (IoT), and Big Data have become pivotal drivers of educational innovation, redefining how learning is personalized, monitored, and scaled. This systematic literature review investigates how these emerging technologies are shaping personalized learning by conducting a comprehensive SWOT analysis based on twenty-four peer-reviewed studies published between 2020 and 2025, selected according to the PRISMA framework. The analysis reveals significant strengths, including AI-enabled adaptive learning pathways, intelligent feedback systems, and real-time analytics that enhance student engagement and learning outcomes. Conversely, major weaknesses persist, such as high implementation costs, limited data interoperability, and insufficient digital readiness among educators. On the opportunity side, the findings point to the potential for interoperable data ecosystems, modular AI-supported pedagogical designs, and the development of scalable smart learning environments. However, several threats remain most notably data privacy vulnerabilities, algorithmic bias, and a growing digital divide across institutions. The review concludes that achieving the transformative promise of these technologies requires a holistic and ethically grounded strategy that prioritizes data governance, equity, and teacher empowerment. Such an approach is essential to ensure that technology-enhanced learning evolves into an inclusive and sustainable educational paradigm.