Optimizing Playtesting

Brief

Playtesting is a game designer’s primary tool to access the quality of his/her game, i.e., understand the players’ experiences. There are a multitude of ways to collect playtesting data which includes gameplay/think-aloud videos, observations, interviews, questionnaires, telemetry and physiological responses. Trying to use all or even some of these data can get confusing very quickly. Many questions are still open including:

- Are physiological signals worth the effort? And which ones?
- Which (combination of) data is better for different genres?
- How to effectively combine different concoctions of data?

The goal of this research is to evaluate current approaches, establish ways to effectively combine them as well as propose supplementary methods using non-intrusive automated techniques that can enhance current methods. The prospects of pursuing this research is hence advantageous to the game design community.

Potential research directions include generating tools for combining different modes of data, as well as using novel data like facial expressions, voice and body language recognition and analysis. This will hence require a variety of techniques in computer vision and machine learning.

Members

Chek Tien Tan
Songjia Shen
Tuck Wah Leong
Daniel Rosser
Yusuf Pisan
Sander Bakkes (University of Amsterdam, Netherlands)
Pejman Mirza-Babaei (University of Ontario Institute of Technology, Canada)
Veronica Zammitto (Electronic Arts, Canada)
Alessandro Canossa (Northeastern University, US)

Outputs

C. T. Tan, T. W. Leong, S. Shen, C. Dubravs, C. Si, “Exploring Gameplay Experiences on the Oculus Rift,” in Proc. CHI PLAY 2015, ACM Press. [pdf]

C. T. Tan, T. W. Leong, and S. Shen, “Combining Think-aloud and Physiological Data to Understand Video Game Experiences,” in Proc. CHI 2014, 2014. [pdf][prezi]

C. T. Tan, S. Bakkes, and Y. Pisan, “Inferring Player Experiences Using Facial Expressions Analysis,” In Proceedings of the 10th Australian Conference on Interactive Entertainment. ACM Press, 2014. [pdf]

C. T. Tan, S. Bakkes, and Y. Pisan, “Correlation between Facial Expressions and the Game Experience Questionnaire,” Entertainment Computing – ICEC 2014, iss. 1, pp. 2-4, 2014.

P. M. Blom, S. Bakkes, C. T. Tan, S. Whiteson, D. Roijers, R. Valenti, and T. Gevers, “Towards Personalised Gaming via Facial Expression Recognition,” in Proceedings of Tenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, Palo, 2014.

S. Shen, C. T. Tan, and T. W. Leong, “Towards Better Tools to Support Mixed Methods in Game User Research,” in Proceedings of CHI 2014 Workshop on Game User Experience, 2014.

C. Tan, D. Rosser, S. Bakkes, and Y. Pisan, “A Feasibility Study in Using Facial Expressions Analysis to Evaluate Player Experiences,” in Proceedings of The Australasian Conference on Interactive Entertainment, 2012.

C. T. Tan and Y. Pisan, “Towards Automated Player Experience Detection With Computer Vision Techniques,” in Proceedings of the CHI Workshop on Game User Research, 2012.

Oct. 26, 2016, 2:52 p.m.