This dissertation explores new possibilities for changing Americans' theories about racism and sexism. Popular American rhetorics of discrimination, and learners' naive models, are focused on individual agents' role in creating bias. These theories do not encompass the systemic and structural aspects of discrimination in American society. When learners can think systemically as well as agentically about bias, they become more likely to support systemic as well as individual remedies. However, shifting from an agentic to a systemic model of discrimination is both cognitively and emotionally challenging. To tackle this difficult task, this dissertation brings together the literature on prejudice reduction and conceptual change to propose using games as an entertainment-based intervention to change players' attribution styles around sexism and racism, as well as their attitudes about the same issues. "Playable model -- anomalous data" theory proposes that games can model complex systems of bias, while instantiating learning mechanics that help players confront the limits of their existing models.;The web-based game Advance was designed using playable model---anomalous data theory, and was used to investigate three questions. First, can a playable model---anomalous data game change players' likelihood of using systemic explanations for bias, and how does it compare to the effectiveness of a control text? Second, how does the game change players' attitudes as compared to a control text? Finally, are there differences between three different versions of the game that offer players different rewards for investigating the bias in the game system?;Advance did not outperform the control text at changing players' likelihood of using systemic attributions for racism and sexism, nor did it outperform the control text in changing players' attitudes. However, significant differences were found between White and non-White player populations in their sensitivity to the different game conditions. White players were unaffected by differences between versions of the game, while non-White players showed differences in play behaviors, in systemic attribution likelihood, and in attitude. Given that White Americans may have more entrenched ideas about discrimination in America, we consider the impacts of the game on non-White player populations as an indicator of what future development of playable model---anomalous data games may be able to achieve.
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