Paper Info
Title
Visualizing event sequence game data to understand player’s skill growth through behavior complexity
Abstract
Analysis of game data is used to study player behavior. For puzzle-based games where solutions are usually defined by their action sequences, player behavior can also be studied by their solution complexity. In this paper, we present a visualization system to help learning expert to understand how actions, timing and the resulting strategy change with regard to the solution complexity. To establish a novel perspective into the patterns not only in action choices but also in behavior complexity, we designed an interactive, customized line chart to track how complexity and performance change at each stage of skill acquisition. Specialized glyph system (Strategy Signature) is implemented to find strategy differences easily with simple visual cues. Contextual information can be explored by switching the view modes to see potential links between complexity and raw attributes. Evaluation with expert users shows that the system effectively reduced their time and effort in finding interesting subgroups and gave them unexplored angles of behavior complexity to contemplate player’s skill growth. In summary, this paper illustrates a visualization approach to enable analysis into the subtleties of behavior complexity in video games.
Year
DOI
Venue
2019
10.1007/s12650-019-00566-5
Journal of Visualization
Keywords
Field
DocType
Game visualization, Event sequence, Information theory, Application
Glyph,Information theory,Sensory cue,Contextual information,Line chart,Visualization,Dreyfus model of skill acquisition,Human–computer interaction,Event sequence,Classical mechanics,Physics
Journal
Volume
Issue
ISSN
22
4
1343-8875
Citations 
PageRank 
References 
1
0.34
0
Authors
4
Name
Order
Citations
PageRank
Wei Li110.34
Mathias Funk211229.69
Quan Li3245.04
Aarnout Brombacher425238.77