Abstract
Wearable sensor technology is increasingly being integrated into educational settings, offering innovative approaches to enhance teaching and learning experiences. These devices track various physiological and environmental variables, providing valuable insights into student engagement, comprehension, and educational environments. However, the extensive and continuous data streams generated by these sensors create significant challenges for learning analytics. This paper presents a comprehensive review of research on learning analytics incorporating wearable technology, systematically identifying methods and approaches that address wearable sensor data challenges. We begin with a systematic review of wearable sensor technologies' historical development and the current state of sensor data in learning analytics. We then examine multimodal sensor applications in learning analytics and propose research and application trends aligned with educational development needs. Our analysis identifies three key challenges: ethical considerations, explainable learning analytics, and technological and data management issues. The paper concludes by outlining seven future development directions for wearable sensors in educational contexts.