Mixed Agents Virtual Observation Lenses for Immersive Learning Environments

Abstract

3-D virtual worlds and other immersive environments offer features that other learning systems cannot easily replicate. As such, they have the potential to revolutionise the way in which people learn. They are well suited to visualise 3-D objects and their relations to explain complex phenomena. In addition, they enable practical experiments to be performed that are difficult to conduct in the real world. They can also help to facilitate collaborative learning in real-time and enable students to become fully engaged in what they are doing. However, these environments require further exploration to improve their learning affordances. For instance, assessing students' performance and collecting learning evidence is still in its early stages. This paper is primarily devoted to furthering our understanding of observation and assessment. In so doing, a virtual observation model has been developed to effectively map classroom-based observations with how people can be evaluated in virtual 3-D environments. The observation model has been applied to a multi-user virtual environment (MUVE) and examples that illustrate its potential effectiveness are provided. In essence, our research aims to support and enhance the learning experience by demonstrating the advantages of 3-D virtual worlds as a means for advancing learning processes