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

This dataset contains the supplementary materials to our publication "Collaborative Problem Solving in Mixed Reality: A Study on Visual Graph Analysis", where we report on a study we conducted. Please refer to publication for more details, also the abstract can be found at the end of this description. The dataset contains:

<ol>
<li>The collection of graphs with layout used in the study</li>
<li> The final, randomized experiment files used in the study</li>
<li>The source code of the study prototype</li>
<li>The collected, anonymized data in tabular form</li>
<li>The code for the statistical analysis</li>
<li>The Supplemental Materials PDF</li>
<li>The documents used in the study procedure (English, Italian, German)</li>
</ol>

<b>Paper abstract:</b>
Problem solving is a composite cognitive process, invoking a number of cognitive mechanisms, such as perception and memory.
Individuals may form collectives to solve a given problem together in collaboration, especially when complexity is perceived to be high.
To determine if and when collaborative problem solving is desired in the context of visual graph analysis, we compare ad hoc pairs to individuals and nominal pairs, when solving different tasks in mixed reality.
We discuss the results of an experiment with 72 participants performed in two countries and three languages.
We apply the concept of task instance complexity to quantify the visual demand of tasks used in the experiment.
Our results show the importance of using nominal groups as a benchmark for evaluating collaborative virtual environments.
We conclude that 3D graph representation is not sufficient to induce better collaborative results compared to the benchmark.