Exporing the Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects

The rapid progress in wearable sensor technology has led to its growing integration into educational settings, offering new avenues for enhancing teaching and learning experiences. These devices, capable of tracking a wide array of physiological and environmental variables, have the potential to provide insights into student engagement, comprehension, and overall educational environments. However, the vast and continuous stream of data generated by these sensors presents substantial challenges for learning analytics. Therefore, the aim of this paper is to provide a comprehensive review of the existing body of research on learning analytics that incorporates wearable technology. By systematically examining studies conducted in this area, the paper seeks to identify the methods and approaches that have been employed to overcome the challenges posed by wearable sensor data. This paper initially conducts a systematic review of the historical development of Wearable Sensor Technologies and the current state of Sensors Data in Learning Analytics. It then examines the application of Multimode sensors in the field of Learning Analytics, subsequently proposing research and application trends in response to the demands of educational development. The paper identifies three primary challenges: Ethical issues, Explainable Learning Analytics, and Technological and Data Challenges. Finally, the paper outlines eight directions for the future development of Wearable Sensors.