Development of Cognitive Symbiosis in Virtual Agents to Improve Remote Classroom Learning Outcomes

在本财政年度，我们已经开始开发该项目的几个基本部分。这包括虚拟形象的设计以及测试，以确定虚拟形象是否会引起用户的某些反应。这些虚拟人物具有各种情绪状态，可以应用于远程学习环境。使用唇形追踪器，我们还可以复制和跟踪远程参与者的面部表情。我们还设计了一个远程交互环境，在这个环境中，教师和学生之间的相互凝视可以在远程能力中可视化。教师获得远程环境和用户在该环境中的微型版本。该系统已经促进了对场景中不同物体的相互抓取和凝视，这些物体最终将成为远程参与者与之互动的学习或培训材料。最后，我们继续致力于开发更好的模型，用于在教育和个人学习背景下对文本的理解进行分类。这包括对支持向量机和随机森林算法的探索，以对长时间学习和研究中的困难进行分类。分类的重点是基于文本的学习，我们假设最终可以应用于3D学习。

In this fiscal year, we have begun to develop several fundamental parts of the project. This includes the design of avatars as well as tests to determine whether the avatars elicit certain responses in users. The avatars are rigged with various emotional states, which can be applied in the remote learning environment. Using the lip trackers, we can also replicate and track remote participant facial expressions.We have also designed a remote interaction environment in which mutual gaze can be visualized between an instructor and student in a remote capacity. The instructor obtains a miniature version of both the remote environment and the user within that environment. The system already facilitates mutual grasping of and gaze onto different objects within the scene, which will eventually be the learning or training materials with which the remote participants interact.Lastly, we have continued our work on developing better models for classifying the understanding of texts in the context of education and personal study. This included the exploration of support vector machines and random forest algorithms to classify difficulties during long periods of learning and studying. The classification is focused on text-based learning, which we hypothesize can eventually be applied to 3D learning.