Don Quixote

Period: 2012 ~ 2014
Grant: Ministry of Knowledge Economy
Budget: $120,000
Partner: Wisepole (Human Resource Company)




The limitations of self-report questionnaires and interview methods for assessing individual differences in human cognitive biases have become increasingly apparent. These limitations have led to a renewed interest in alternative modes of assessment, including for implicit and explicit aspects of human behavior (i.e., dual-process theory). Acknowledging this, the present study was conducted to develop and validate a serious game, “Don Quixote,” for measuring specific cognitive biases: the bandwagon effect and optimism bias. We hypothesized that the implicit and explicit game data would mirror the results from an interview and questionnaire, respectively.

To examine this hypothesis, participants (n = 135) played the serious game and completed a questionnaire and interview in a random order for cross-validation. The results suggest that the serious game and the underlying intrinsic nature of its game mechanics (i.e., evoking instant responses under time pressure) are of importance for the further development of cognitive bias measures in both academia and practice.




  • Defined cognitive biases that affect decision-making (inter alia, bandwagon effect and optimism bias)
  • Developed scenario-based serious games to collect behavioral data
  • Analyzed behavioral data to find meaningful patterns of decision-making triggered by game elements
  • Tools: Game analytics, exploratory data analysis, prediction using regression









Published by

Kyoungwon Seo

Kyoungwon Seo is an Assistant Professor in the Dept. of Applied Artificial Intelligence at Seoul National University of Science and Technology (SeoulTech). His research focuses on designing reliable, safe and trustworthy AI systems using theories and methods from human-computer interaction, deep learning, and virtual reality. He deploys and evaluates these AI systems in real world contexts (e.g., classrooms, hospitals) where he can obtain ecologically valid user data. He is collaborating with industrial and academic partners such as Microsoft, Hyundai Motor Company, and Hanyang Medical Center.

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