The rapid development of smart and mobile technologies—including artificial intelligence (AI), machine learning, the Internet of Things (IoT), and wearable devices—has significantly transformed education. Educational institutions are evolving into smart campuses and smart learning environments, leveraging these technologies to support blended and personalized learning for on-campus, remote, and off-campus students. Smart learning environments facilitate interactive and engaging learning experiences, accommodate diverse learner needs, and support skill-based education to address digital workforce gaps. Despite these advancements, there is a lack of a structured framework for evaluating the effectiveness, usability, and pedagogical impact of smart learning environments.This study aims to develop a comprehensive theoretical model for evaluating smart learning environments, identifying and analyzing factors that influence their adoption, implementation, and effectiveness. Drawing from literature on smart campuses, intelligent learning systems, and technology-enhanced education, the study proposes a model integrating technological, pedagogical, and contextual factors to guide assessment and implementation decisions. By providing a structured evaluation framework, this research supports educators, administrators, and policymakers in designing inclusive, effective, and scalable smart learning environments. The model also provides insights into the relationship between technological integration, learner engagement, and learning outcomes, offering a foundation for evidence-based decision-making in modern educational settings
Abdullahi et al. (Fri,) studied this question.