论文标题
元学习环境:测量,预测和改善人际效果
Metaversal Learning Environments: Measuring, predicting and improving interpersonal effectiveness
论文作者
论文摘要
众所周知,体验式学习是个人和专业发展的一种引人入胜且有效的方式。该元评估为创建可能发生这种体验式学习的环境提供了足够的机会。在这项工作中,我们介绍了一种新颖的体系结构,将人工智能和虚拟现实结合在一起,以创造一种使用化身的高度沉浸式和高效的学习体验。该框架使我们能够测量个人与头像互动的人际交往有效性。我们首先提出了一项小型试点研究及其用于增强框架的结果。然后,我们使用增强的框架提出了一项更大的研究,以测量,评估和预测个人与化身相互作用的人际交往有效性。结果表明,在人际关系上缺陷的人在与化身进行多次相互作用后表现出表现的显着改善。结果还表明,个人在此框架内与化身自然互动,并表现出与现实世界中类似的行为特征。我们以此为基础来分析这些互动过程中个人的基本音频和视频数据流。最后,我们从这些数据中提取相关特征,并提出一种基于机器学习的方法,以预测人类瓦塔尔对话期间人际关系的有效性。我们通过讨论这些发现对为现实世界构建有益应用的含义来总结。
Experiential learning has been known to be an engaging and effective modality for personal and professional development. The Metaverse provides ample opportunities for the creation of environments in which such experiential learning can occur. In this work, we introduce a novel architecture that combines Artificial intelligence and Virtual Reality to create a highly immersive and efficient learning experience using avatars. The framework allows us to measure the interpersonal effectiveness of an individual interacting with the avatar. We first present a small pilot study and its results which were used to enhance the framework. We then present a larger study using the enhanced framework to measure, assess, and predict the interpersonal effectiveness of individuals interacting with an avatar. Results reveal that individuals with deficits in their interpersonal effectiveness show a significant improvement in performance after multiple interactions with an avatar. The results also reveal that individuals interact naturally with avatars within this framework, and exhibit similar behavioral traits as they would in the real world. We use this as a basis to analyze the underlying audio and video data streams of individuals during these interactions. Finally, we extract relevant features from these data and present a machine-learning based approach to predict interpersonal effectiveness during human-avatar conversation. We conclude by discussing the implications of these findings to build beneficial applications for the real world.