Does emotion influence visual perception? Depends on how you look at it

ABSTRACT

One of the biggest challenges in the study of emotion–cognition interaction is addressing the question of whether and how emotions influence processes of perception as distinct from other higher-level cognitive processes. Most theories of emotion agree that an emotion episode begins with a sensory experience – such as a visual percept – that elicits a cascade of affective, cognitive, physiological, and/or behavioural responses (the ordering and inclusion of those latter components being forever debated). However, for decades, a subset of philosophers and scientists have suggested that the presumed perception → emotion relationship is in fact bidirectional, with emotion also altering the perceptual process. In the present review we reflect on the history and empirical support (or, some might argue, lack thereof) for the notion that emotion influences visual perception. We examine ways in which researchers have attempted to test the question, and the ways in which this pursuit is so difficult. As is the case with the ongoing debate about the cognitive penetrability of perception, we conclude that nothing is conclusive in the debate about the emotional penetrability of perception. We nonetheless don rose-coloured glasses as we look forward to the future of this research topic.     

Identifying Misfitting Achievement Estimates in Performance Assessments: An Illustration Using Rasch and Mokken Scale Analyses

Researchers apply individual person fit analyses as a procedure for checking model-data fit for individual test-takers. When a test-taker misfits, it means that the inferences from their test score regarding what they know and can do may not be accurate. One problem in applying individual person fit procedures in practice is the question of how much misfit it takes to make the test score an untrustworthy estimate of achievement. In this paper, we argue that if a person’s responses generally follow a monotonic pattern, the resulting test score is “good enough” to be interpreted and used. We present an approach that applies statistical procedures from the Rasch and Mokken measurement perspectives to examine individual person fit based on this good enough criterion in real data from a performance assessment. We discuss how these perspectives may facilitate thinking about applying individual person fit procedures in practice.