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ICG JKU Linz Lab Talk: 'Visualization of Mixed Playtesting Data', Günter Wallner
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Data collected through Games User Research (GUR) is constantly growing in volume. Moreover, playtesting frequently results in multi-modal datasets consisting of qualitative and quantitative data. Simultaneously displaying mixed playtesting data can offer additional benefits for user researchers as it can provide relevant contextual information. This talk will show how visualizations can be helpful for interpreting (mixed) GUR datasets.
The presentation will start with a high-level discussion of the benefits of visualization for analyzing playtesting data. Afterwards, possible ways of visualizing individual player data will be introduced. The talk will then demonstrate different aggregation techniques for different types of playtesting data (movement, discrete events, and continuous player-related variables such as health or physiological measurements) to convey common patterns and outliers. Aggregation techniques can be very helpful when dealing with larger datasets to avoid difficult to read visualizations. The presented techniques can be applied individually or in combination to triangulate the different data types.
Lastly, the talk will address a thus-far mostly neglected issue in GUR, namely how visual design choices for data visualizations can impact the interpretation of gameplay data. An inappropriate visual design can be misleading, result in wrong conclusions, and have practical consequences. Attendees will come away with an understanding of how visualizations can help in understanding playtesting data.
The presentation will start with a high-level discussion of the benefits of visualization for analyzing playtesting data. Afterwards, possible ways of visualizing individual player data will be introduced. The talk will then demonstrate different aggregation techniques for different types of playtesting data (movement, discrete events, and continuous player-related variables such as health or physiological measurements) to convey common patterns and outliers. Aggregation techniques can be very helpful when dealing with larger datasets to avoid difficult to read visualizations. The presented techniques can be applied individually or in combination to triangulate the different data types.
Lastly, the talk will address a thus-far mostly neglected issue in GUR, namely how visual design choices for data visualizations can impact the interpretation of gameplay data. An inappropriate visual design can be misleading, result in wrong conclusions, and have practical consequences. Attendees will come away with an understanding of how visualizations can help in understanding playtesting data.