Educating data-informed citizens: statistical, political and information search efficacies and their interactions

Although recent initiatives in statistics education have emphasized civic and socio-political contexts, little is known about the motivational resources that support engagement with data in public life. This study investigates the relationships among statistical, political, and information-search self-efficacy and examines how these beliefs develop within an interdisciplinary civic statistics intervention. Using a pre–post-test control-group design with pre-service teachers from mathematics and civics programs, we analyzed the development of domain-specific self-efficacy beliefs and students’ appreciation of the role of science in politics. Correlation, Bayesian network, and structural equation modeling analyses revealed that statistical, political, and information-search self-efficacy are moderately related but distinct constructs, with information-search self-efficacy occupying a central position within the network. The intervention produced substantial gains in statistical self-efficacy ( η ² = .12 η 2 = . 12 ) and information-search self-efficacy ( η ² = .11 η 2 = . 11 ), while effects on political self-efficacy were smaller and less robust. In contrast, appreciation of the role of science in politics showed only weak associations with the efficacy variables and remained stable over time, suggesting that it represents a comparatively independent normative orientation. The findings support a multidimensional view of civic statistical literacy that integrates motivational and normative dimensions alongside cognitive competencies. They further demonstrate the potential of interdisciplinary learning environments to strengthen learners’ confidence in engaging with data and information in civic contexts.