Lab-in-the-field experiment in Brazil

Amid a growing influence of misinformation and distrust in traditional news media, questions have been raised about how to improve media literacy education beyond the classroom. Prior studies in media literacy have been effective at improving students’ ability to identify misinformation but have only been conducted in K-12 classrooms (Amar et al., 2025) or have been less rooted in evidence-based pedagogy. Questions remain about how to improve media literacy education, particularly for adults, and to mitigate threats to democracy. This study addresses these challenges by bridging the gap between political science and education research. I argue that evidence-based pedagogical approaches, combined with interactive AI tools, can help individuals recognize biases in their media diets and encourage behavioral change beyond the intervention itself. As individuals become more willing to engage with ideas they may not agree with, they may also become more willing to engage with people they disagree with.

This study tests a series of approaches to teach people how to identify biases in their media diets and understand the value of exposure to cross-cutting media, varying exposure to an AI chatbot and evidence-based teaching methods. Participants will be assigned to one of four conditions that vary in exposure to pedagogy and the use of an AI chatbot.

Primary outcomes include selective exposure and willingness to interact with individuals holding opposing political beliefs, as well as data tracking respondents’ browsing history to see whether the effects measured in the intervention extend to behaviors outside the study. Effects will be measured immediately and at two weeks post-intervention to assess effect duration. I expect that the pedagogy treatment will have the strongest treatment effects, encouraging respondents to vary their media diets and interact with those who hold different political beliefs due to its high levels of interactivity, engagement, and critical thinking.