We present BadgeX, a novel system integrating lightweight wearable IoT devices (smart badges/smartphones) with Large Language Models (LLMs) to enable real-time collaborative learning analytics. The system captures multimodal sensor data (e.g., audio, image, motion, depth) from learners, processes it into structured features, and employs an LLM-driven framework to interpret these features, generating high-level insights grounded in learning theory. A pilot study demonstrated the system's capability to capture rich collaboration traces and for an LLM to produce plausible, theoretically coherent narrative analyses from sensor-derived features. BadgeX aims to lower deployment barriers, making complex collaborative dynamics visible and offering a pathway for real-time support in educational settings.

翻译：我们提出BadgeX，一种新型系统，将轻量级可穿戴物联网设备（智能徽章/智能手机）与大语言模型（LLMs）相结合，以实现实时协作学习分析。该系统从学习者处捕获多模态传感器数据（如音频、图像、运动、深度），将其处理为结构化特征，并采用LLM驱动的框架解读这些特征，生成基于学习理论的高层次洞察。一项初步研究表明，该系统能够捕获丰富的协作轨迹，并使LLM能够从传感器导出的特征中生成合理且理论连贯的叙事性分析。BadgeX旨在降低部署门槛，使复杂的协作动态可见，并为教育环境中的实时支持提供途径。