Dark Pattern: A Serious Game for Learning About the Dangers of Sharing Data

This exploratory study examines whether the board game "Dark Patterns," designed to teach high school students about manipulative data-collection interface tricks, can meaningfully change how young people understand and protect their personal data. The research involved 56 students aged 16 to 18 in Norway and Denmark, analyzed using partial least squares structural equation modeling (PLS-SEM). The authors' central finding is that playing the game produced only limited gains in students' knowledge of dark patterns, though that knowledge proved to be the strongest predictor of an intention to protect personal data.

Among the most notable results, players recognized only one of five dark pattern types with confidence, Disguised Ads at roughly 57 percent, and most respondents expressed no plans to take proactive data-protection steps. Roach Motel and Disguised Ads were rated as the most harmful patterns. Dark pattern knowledge and perceived risk together explained a moderate 33 to 40 percent of the variance in protective intentions, while gender did not significantly predict those intentions. The Roach Motel and privacy-zuckering measures showed reliability problems, which the authors flag as a limitation.

The study's scope is narrow: a small, geographically confined sample of Nordic adolescents, with a focus on a single serious game and a short-term outcome window. The accompanying research base draws on established PLS-SEM methodology, the privacy paradox literature, and prior work on serious games for education, with the game's design rooted in analytic approaches to privacy decision-making. Taken together, the findings suggest that serious games can build awareness of data-collection manipulation, but that a single play session yields partial rather than comprehensive understanding.