# Metaversal Learning Environments: Measuring, predicting and improving interpersonal effectiveness

**Authors:** Arjun Nagendran, Scott Compton, William Follette, Artem Golenchenko, Anna Compton, Jonathan Grizou  
**arXiv:** [2205.02875](https://arxiv.org/abs/2205.02875)  
**Date:** 2022-05-05  
**Summary page:** https://www.summarizepaper.com/en/paper/2205.02875v1/

## Key points

- Paper explores use of experiential learning in the Metaverse for personal and professional development
- Introduces architecture combining AI and VR to create immersive learning experiences using avatars
- Framework allows measurement of interpersonal effectiveness during interactions with avatars
- Small pilot study conducted, leading to improvements in the framework
- Larger study conducted to measure, assess, and predict interpersonal effectiveness with avatars
- Individuals with deficits in interpersonal effectiveness show improvement after interacting with avatars
- Individuals interact naturally with avatars and exhibit similar behavioral traits as real-world interactions
- Audio and video data streams analyzed to extract relevant features for predicting interpersonal effectiveness
- AI and VR technologies can create beneficial applications for real-world scenarios, improving interpersonal skills and performance
- Implications for education, training, therapy, and communication fields.

## Summary

The paper titled "Metaversal Learning Environments: Measuring, predicting and improving interpersonal effectiveness" explores the use of experiential learning in the Metaverse to enhance personal and professional development. The authors introduce a novel architecture that combines Artificial Intelligence (AI) and Virtual Reality (VR) to create immersive learning experiences using avatars. The framework allows for the measurement of interpersonal effectiveness during interactions with avatars. A small pilot study is conducted to provide initial results that are used to improve the framework. Building upon these improvements, a larger study is conducted to measure, assess, and predict the interpersonal effectiveness of individuals interacting with avatars. The findings reveal that individuals who initially have deficits in their interpersonal effectiveness show significant improvement after multiple interactions with avatars. Furthermore, the results demonstrate that individuals interact naturally with avatars within this framework and exhibit similar behavioral traits as they would in real-world interactions. To gain deeper insights into these interactions, audio and video data streams captured during experiments are analyzed to extract relevant features from this data which are then used to present a machine-learning based approach for predicting interpersonal effectiveness during human-avatar conversations. In conclusion, the research highlights the potential of using AI and VR technologies in creating beneficial applications for real-world scenarios by leveraging experiential learning in Metaversal environments which can help individuals improve their interpersonal skills and enhance their overall performance. These findings have implications for various fields such as education, training, therapy, and communication.