Visualizing Behavioral Data from a 3D Virtual Learning Environment: A Preliminary Study
Matthew Schmidt, James M. Laffey · 2012
This paper describes a preliminary study which attempted to apply learning analytics methods to usage data generated by students with autism spectrum disorders using iSocial, a collaborative, three-dimensional virtual learning environment. Drawing from similar methods in the area of learning and content management systems, the work presented in this paper considers two types of user behaviors that are not present in LMS/CMS and are unique to 3D VLEs: avatar movement and spoken dialogue. The method developed for capturing avatar movements and spoken dialogue and writing these data to a log file is explained, along with a description of the process the research team underwent in order to transform the log data into graphical depictions of user behavior over time. Examples of five different visualization types are examined. Conclusions and directions for future research are provided.