Rethinking Media Literacy: A Dual-Indicator Approach to Misinformation Detection in Higher Education

Topic
This thesis investigates how misinformation detection can be measured more effectively among students in Swiss higher education. It introduces a dual indicator model that combines self-reported cognitive dispositions such as cognitive reflection and receptivity to pseudo profound statements with a performance-based task requiring the classification of manipulated news headlines. The study examines how these two types of indicators relate to each other and to students' ability to critically evaluate digital content, contributing to the development of more valid tools for assessing evaluative competence in digital media literacy.

Relevance
As students increasingly encounter digital content across educational and social platforms, their ability to judge the credibility of information becomes a crucial skill. While existing research has explored media literacy from various perspectives, there is still a need for assessment models that better reflect how well individuals perform in identifying misleading content. This thesis addresses that gap by investigating how self-reported dispositions and task-based accuracy can be integrated into a combined measurement approach. The results lay the groundwork for developing more targeted tools to assess evaluative competence in higher education settings.

Results
The findings demonstrate that the two components of the dual-indicator model contribute differently to students’ ability to detect misinformation. Receptivity to pseudo-profound statements showed a strong negative association with detection accuracy, suggesting that students more inclined to accepting vague or superficially meaningful content were less effective at identifying manipulated headlines. Cognitive reflection was positively associated with detection accuracy, though its effect became evident only when behavioral variables were taken into account. These results indicate that combining self-reported dispositions with performance-based tasks provides a more differentiated understanding of evaluative competence in digital media contexts.

Implications for practitioners

• Use a combination of cognitive trait measures and task-based performance to evaluate students’ ability to detect misinformation.
• Incorporate bullshit receptivity as an indicator when identifying students' susceptibility to manipulated content.
• Develop digital literacy programs that address both cognitive tendencies and media engagement habits.
• Use the dual-indicator framework as a foundation for designing targeted assessment and training tools in higher education.

Methods
This study used a cross-sectional online survey targeting students enrolled in Swiss higher education institutions. A total of 123 participants completed validated instruments measuring cognitive reflection and bullshit receptivity, followed by a task that required classifying manipulated and authentic news headlines. Behavioral and demographic variables were also recorded to contextualize the findings. Regression analyses were applied to test the relationship between cognitive traits, behavioral patterns, and detection performance, and to evaluate how well these factors jointly predict evaluative competence.