Mixed Reality for Collaborative Learning and Collaborative Problem Solving Environment

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Mixed Reality for Collaborative Learning and Collaborative Problem 
Solving Environment"

By

Mr. Santawat THANYADIT


Abstract

People often rely on workspace awareness to collaborate with one another, 
especially in learning and problem-solving tasks. Workspace awareness is 
defined as an understanding of a current state of the work environment and 
collaborators' activities. However, workspace awareness is difficult to 
maintain in virtual environments (VE), since some information from the real 
world is missing. Fortunately, VEs are flexible and can be designed to 
compensate for a lack of real world cues. This thesis aims to improve 
collaborative workspace awareness through enhancing the design of VEs. Our 
proposed approaches improve workspace awareness in three ways. The first 
approach examines space configurations that could improve awareness in a 
collaboration. The second explores different strategies for updating the visual 
environment so that users are aware of their collaborators' actions. The third 
focuses on finding visual cues that raise the user's awareness when 
collaborating with multiple users. Prior research studies suggested that users 
operate in workspace to manage their attention and divide their tasks when 
working in the real world. The space within the users' reach is often assigned 
as a private space and the space out of users' reach is assigned as a group 
space. Following this approach, we propose to set up a virtual space in a 
desktop virtual reality environment by assigning the space in front of the 
desktop screen as a private space and the space behind the screen as a group 
space. According to our user study, this setup improves collaborations between 
users.

To gain further insight into information sharing strategies in VEs, a user 
study was conducted to compare different strategies for updating the VEs in 
complex remote problem-solving tasks. From the study, real-time updating is 
found to be not suitable for workspace awareness, especially when users are 
performing different tasks. On the other hand, an updating strategy that 
updates only information that is relevant to the users' actions performs the 
best. Moreover, users change collaboration strategies depending on the update 
timing. Design guidelines are proposed from the user study as a direction for 
different collaborative situations.

While there are many research works that allow users to work together in 
one-to-one collaborations, less attention has been paid to one-to-many 
collaborations. This is due to the lack of visual awareness cues that allow 
users to spectate multiple users. To alleviate this limitation, a prototype 
system named ObserVAR is proposed. ObserVAR utilizes Augmented Reality (AR) 
technology to help an instructor in spectating multiple Virtual Reality (VR) 
users by augmenting the instructor's environment with virtual awareness cues 
generated from the VR users. In the development of ObserVAR, different 
awareness cues are compared in a user study to determine its suitability under 
various circumstances. The virtual awareness cues are then optimized further 
using techniques derived from graph visualization to reduce visual clutter.

Finally, the knowledge gained from improving workspace awareness using 
different approaches is used to formulate a collaborative framework for 
learning and problem-solving tasks. The contributions of this thesis include an 
enhanced design of desktop virtual reality for collaborations; multiple 
improvements in workspace awareness across different aspects; the design and 
development of the ObserVAR system for one-to-many collaborations; and a 
framework for collaborative problem-solving that utilizes the proposed designs. 
This thesis explores various enhancements of VEs, which lead to a better 
performance in collaborative learning and problem-solving tasks. The VE designs 
in this thesis can be used as guidelines for future collaborative 
problem-solving systems.


Date:			Monday, 26 August 2019

Time:			1:00pm - 3:00pm

Venue:			Room 6581
 			Lifts 27/28

Chairman:		Prof. Ying ZHAO (MARK)

Committee Members:	Prof. Ting Chuen PONG (Supervisor)
 			Prof. Xiaojuan MA
 			Prof. Huamin QU
 			Prof. Ravindra Stephen GOONETILLEKE (ISD)
 			Prof. Chong Wah NGO (CityU)


**** ALL are Welcome ****