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The "curse of knowledge" when predicting others' knowledge
Jonathan G Tullis1, Brennen Feder2
1Department of Educational Psychology, University of Arizona, 1430 E. Second St., Tucson, AZ, 85721, USA. tullis@arizona.edu.
Abstract:
To succeed in a social world, we must be able to accurately estimate what others know. For example, teachers must anticipate student knowledge to plan lessons and communicate effectively. Yet one's own knowledge consistently contaminates estimates about others' knowledge. We examine how one's knowledge influences the calibration and resolution of participants' estimates of novices' knowledge. Across four experiments, participants studied trivia questions and estimated the percentage of novice participants who would know the answer across multiple study/estimation rounds. When participants were required to answer the question before estimating what novices would know, studying the facts impaired both the calibration and resolution of the estimates. Studying the facts reduced the validity of one's experiences for predicting novices' knowledge, and estimators utilized their own experiences less when predicting novices' knowledge as they studied. Experimentally reducing reliance on one's own knowledge did not improve the accuracy of estimates. The results suggest that learning impairs the accuracy of judgments of others' knowledge, not because estimators rely too heavily on their own experiences, but because estimators lack diagnostic cues about others' knowledge.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.