Predicting others’ knowledge: Knowledge estimation as cue utilization

Abstract

Predicting what others know is vital to countless social and educational interactions. For example, the ability of teachers to accurately estimate what knowledge students have has been identified as a crucial component of effective teaching. I propose the knowledge estimation as cue-utilization framework, in which judges use a variety of available and salient metacognitive cues to estimate what others know. In three experiments, I tested three hypotheses of this framework: namely, that participants do not automatically ground estimates of others' knowledge in their own knowledge, that judgment conditions shift how participants weight different cues, and that participants differentially weight cues based upon their diagnosticity. Predictions of others' knowledge were dynamically generated by judges who weighed a variety of available and salient cues. Just as the accuracy of metacognitive monitoring of one's own learning depends upon the conditions under which judgments of self are elicited, the bases and accuracy of metacognitive judgments for others depends upon the conditions under which they are elicited.