The integration of the Internet of Things (IoT) in education has fundamentally transformed personalized online learning (POL), enabling adaptive, context-aware environments that tailor learning based on real-time environmental data or device usage. This approach fosters learner-centered environments that customize content and pace according to individual needs and preferences. All are powered by interconnected devices and data analysis. This review systematically explores various technological and pedagogical approaches to integrate IoT in POL systems, including devices, communication technologies, context-aware mechanisms, integration frameworks, computing technologies, and implemented pedagogical methods. By examining 61 peer-reviewed studies, this research categorizes IoT technological and pedagogical approaches, evaluates their impacts on personalization, and identifies challenges such as data privacy and resource constraints. The key findings explore how IoT-enhanced POL significantly improves learner engagement, adaptive learning, and academic outcomes, assessed via performance analytics, tests, and questionnaires. However, gaps in interoperability standards, learner profiling, cognitive load modeling, and the ethical use of data highlight the need for a unified framework. In addition, it emphasizes the transformative potential of IoT in creating personalized and inclusive learning environments. The study concludes by proposing an IoT-based POL framework and recommends directions for future research and practical applications.

Background: The integration of the Internet of Things (IoT) in education has trans-formed Personalized Online Learning (POL), enabling adaptive, context aware and learner-centered environments through interconnected devices and real-time data anal-ysis; Methods: This review systematically explores various IoT integration technological and pedagogical approaches in POL systems, including things, communication tech-nologies, context-aware mechanisms, integration frameworks, computing technologies and implemented pedagogical approaches. By examining 61 peer-reviewed studies, the study categorizes IoT technological and pedagogical approaches, evaluates their impact on personalization and identifies challenges such as data privacy and resource con-straints; Results: Key findings reveal that IoT-enhanced POL can significantly improve learner engagement, adaptive learning and academic outcomes; Conclusions: Gaps in interoperability standards, learner profiling, cognitive load modeling and the ethical use of data highlight the need for a unified framework. The paper concludes with pro-posing an IoT based POL framework and recommendations for future research and practical applications, emphasizing IoT’s transformative potential in creating personal-ized and inclusive learning environments.