Social and Behavioral Sciences Commons^™

How Random Noise And A Graphical Convention Subverted Behavioral Scientists' Explanations Of Self-Assessment Data: Numeracy Underlies Better Alternatives, Edward Nuhfer, Steven Fleisher, Christopher Cogan, Karl Wirth, Eric Gaze

Numeracy

Despite nearly two decades of research, researchers have not resolved whether people generally perceive their skills accurately or inaccurately. In this paper, we trace this lack of resolution to numeracy, specifically to the frequently overlooked complications that arise from the noisy data produced by the paired measures that researchers employ to determine self-assessment accuracy. To illustrate the complications and ways to resolve them, we employ a large dataset (N = 1154) obtained from paired measures of documented reliability to study self-assessed proficiency in science literacy. We collected demographic information that allowed both criterion-referenced and normative-based analyses of self-assessment data. …