To explain why some severe weather alert graphics draw viewers' attention, while others do not, the current study looks to the Limited Capacity Model of Mediated Motivated Message Processing (LC4MP), Feature Integration Theory, and Dual Processing Theory to examine how cognitive load of the primary task and cueing as a form of weather alert presentation affect visual attention, recognition, cued, and free recall of both the primary and secondary tasks. One of the most basic and effective ways to communicate important information is through the visual system (Palmer, 1999). This paper will identify ways of making visual weather alert graphics more effective.
The paper starts with conceptualization of visual attention mechanisms at the biological level. Next, the paper provides the study's theoretical framework by looking at dual processing theory, LC4MP, and FIT. Third, the study explicates the study's two independent variables – cognitive load of primary task and cueing technique of secondary task – along with proposing the study's hypotheses and research questions. Fourth, the experimental method used in this study and the proposed data-analytic plan are described. Finally, the study's anticipated theoretical and practical implications, as well as future research directions are outlined.
By manipulating the television show's cognitive load (high vs. low) and the weather alert's cueing technique (cued vs. non-cued), this study plans to show how and when viewers' attention and memory shift during these different tasks. This study proposes eye-tracking and self-reported memory measures to understanding these outcomes. Acquiring greater viewers' attention will hopefully lead to swifter message processing that will in turn promote more favorable adaptive behavioral outcomes during severe weather events.