Collaborative Problem Solving in Mixed Reality: A Study on Visual Graph Analysis

Area of Science:

• Cognitive Science
• Human-Computer Interaction
• Information Visualization

Background:

• Problem solving is a complex cognitive process involving perception and memory.
• Collaboration is often sought for complex tasks, particularly in visual graph analysis.
• Evaluating collaborative virtual environments requires appropriate benchmarks.

Purpose of the Study:

• To investigate the conditions under which collaborative problem solving is beneficial in mixed reality visual graph analysis.
• To compare the effectiveness of ad hoc pairs, individuals, and nominal pairs in solving visual graph analysis tasks.
• To assess the impact of task complexity on collaborative decision-making.

Main Methods:

• An experiment was conducted with 72 participants across two countries and three languages.
• Participants solved various visual graph analysis tasks in a mixed reality environment.
• Task instance complexity was used to quantify the visual demand of the tasks.
• Performance was compared between individuals, ad hoc pairs, and nominal pairs.

Main Results:

• Nominal groups proved essential as a benchmark for evaluating collaborative virtual environments.
• The study found that 3D graph representation alone was insufficient to yield superior collaborative results compared to the benchmark.
• Task complexity influenced the perceived need for collaboration.

Conclusions:

• The effectiveness of collaborative virtual environments in visual graph analysis needs careful evaluation against robust benchmarks.
• Simply employing 3D graph representations does not inherently enhance collaborative problem-solving outcomes.
• Future research should explore factors beyond representation that foster effective collaboration in complex visual tasks.