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Unified Visualization of Quantitative and Qualitative Playtesting Data

Pejman Mirza-Babaei, Günter Wallner, Graham McAllister, and Lennart Nacke. 2014. Unified Visualization of Quantitative and Qualitative Playtesting Data. In Proceedings of CHI EA 2014. Toronto, ON, Canada. ACM, 1363-1368. doi:10.1145/2559206.2581224

PDF DOI BibTeX

@inproceedings{mirza2014unified,
Abstract = {A major challenge in studying player experience is tying together the results of quantitative and qualitative games user research (GUR) data. For example, combining data from players' physiological measures with questionnaire or interview results and in-game movement data into a single report is not straightforward because the underlying data is often in different formats. Visualization techniques can facilitate the understanding of relationships among these data sets. Although various visualization techniques have already been introduced in GUR, most of these techniques only focus on displaying large amounts of data captured directly via telemetry without integrating qualitative or contextual data on players' emotional experience. Hence, here we propose a novel visualization approach to triangulate the above mentioned mixed data sources.},
Address = {Toronto, ON, Canada},
Author = {P. Mirza-Babaei, G. Wallner, G. McAllister, and L. E. Nacke},
Booktitle = {Proceedings of chi ea 2014},
Doi = {10.1145/2559206.2581224},
Img = {http://hcigames.com/wp-content/uploads/2015/02/Unified-Visualization-of-Quantitative-and-Qualitative-Playtesting-Data.png},
Organization = {ACM},
Pages = {1363-1368},
Publisher = {ACM},
Title = {Unified Visualization of Quantitative and Qualitative Playtesting Data},
Url = {https://hcigames.com/download/unified-visualization-of-quantitative-and-qualitative-playtesting-data},
Year = {2014},

Abstract

A major challenge in studying player experience is tying together the results of quantitative and qualitative games user research (GUR) data. For example, combining data from players' physiological measures with questionnaire or interview results and in-game movement data into a single report is not straightforward because the underlying data is often in different formats. Visualization techniques can facilitate the understanding of relationships among these data sets. Although various visualization techniques have already been introduced in GUR, most of these techniques only focus on displaying large amounts of data captured directly via telemetry without integrating qualitative or contextual data on players' emotional experience. Hence, here we propose a novel visualization approach to triangulate the above mentioned mixed data sources.