Knowledge Monitoring Calibration: Sensitivity and Specificity as Unique Cognitive Constructs

Francis SmithUniversity of Iowa
Christopher WasKent State University

Abstract

Knowledge monitoring is an important metacognitive process which can help students improve study habits and thereby increase academic performance. Which is more useful in predicting test performance: knowing what you know, or knowing what you do not know? Two distinct constructs of knowledge monitoring calibration, sensitivity and specificity, were used along with the more traditional Gamma to predict performance on tests in an undergraduate educational psychology course. It was found that sensitivity, a measure of correctly identifying known items, was the most useful in predicting overall test scores as well as final exam scores. Specificity, on the other hand, had no significant impact on exam performance. Results suggest that sensitivity and specificity may be more meaningful measures of knowledge monitoring calibration when it comes to predicting academic achievement, as well as being better adapted for missing values in any one cell of the data.

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