小组协作学习中社会交互过程及其对于知识构建的贡献无法直接测量，教师无法将行为观察、学习效果和不可见的认知活动融合起来理解协作学习的过程与效果。拟申请项目结合脑电超扫描（跨脑采集）与情感式脑机交互技术，提供一种新方法实时监测协作学习的两个关键指标：认知投入度与概念更新。具体研究内容：(1) 基于局域网的脑电设备间的数据同步与不同设备采集参数的校准技术；(2) 衡量多人脑电数据的人际协变关系的关键指标的计算方法；(3) 协作学习过程关键指标（认知投入）/环节（概念更新）的神经表征与建模技术；(4) 基于多人脑电的协作学习实时监测模型及其可视化技术。本研究从超扫描记录的脑电数据中监测小组成员在协作学习中的深层次的认知神经活动，并映射到学习评价活动。本研究为全过程客观把脉协作学习过程与效果提供了新的技术途径，丰富了学习评价的理论与方法。

As we all know, existing approaches to evaluating collaborative learning tend to focus on students’ observable actions as well as artifacts created during collaboration. Due to the challenge in demonstrating social interactions in collaborative learning and how they foster collaborative knowledge construction, it’s difficult to develop a more coherent method in understanding the collaboration so that we can assess collaborative learning based on both observable actions, products, and invisible cognitive changes made during the process. To tackle this challenge, this research contributes to an innovative approach in assessing small group collaborative through EEG hyperscanning and affective brain-computer interface technology. The purposes of this research are to understanding students’ real-time cognitive engagement and conceptual change in collaborative learning, and establish a tool to evaluate small group learning. Specifically, we will 1) investigate key technology for EEG hyperscanning and interpersonal neural synchronization; 2) elaborate the neural representation of cognitive engagement and conceptual change in collaborative learning; 3) create a model to monitor small group collaboration with EEG hyperscanning; and 4) to examine the relationship between social interactions, cognitive status, and learning achievements. Our research is expected to provide a promising approach in assessing collaborative learning.