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The feeding of knowing refers to predictions about subsequent memory performance on previously nonrecalled items. The most frequently investigated type of subsequent performance has been recognition. The present research explored predictive accuracy with two new feeling-of-knowing criterion tests (in addition to recognition): relearning and perceptual identification. In two experiments, people attempted to recall the answers to general-information questions such as, "What is the capital of Australia?", then made feeling-of-knowing predictions for all nonrecalled answers, and finally had a criterion test to assess the accuracy of the feeling-of-knowing predictions. Experiment 1 demonstrated that perceptual identification can be employed successfully as a criterion test for the feeling of knowing. This opens a new way for metamemory research via perception. Moreover, the feeling-of-knowing accuracy for predicting perceptual identification was not significantly correlated with the feeling-of-knowing accuracy for predicting recognition, in accord with the idea that these two tests assess memory differently. Experiment 2 demonstrated that relearning performance can also be predicted by feeling-of-knowing judgments. Both experiments showed that there is a positive relationship between the feeling of knowing and the amount of time elapsing before a memory search is terminated during recall. Further analyses showed that this relationship is substantial for nonrecalled items for which the person did not guess an answer (omission errors), but the relationship is null or negative for nonrecalled items that the person guessed incorrectly (commission errors). Several theoretical mechanisms that may underlie the feeling of knowing are proposed.

We contrasted several ways that an individual's judgments of learning (JOLs) can be lItilized when allocating additional study ("restudy") during the learning of SwahiliEnglish translation equivalents. The findings demonstrate how metacognitive monitoring can be utilized to benefit multi/rial learning. Computer-colltrolled allocatioll of restudy based on people's JOLs was equivalellt to most people's own allocation ofrestudy (indicating that the computer algorithm can provide a sufficient account ofpeople's allocatioll of restudy) and was more effective than a computer-controlled allocatioll based on normative performance (indicating that people's metacognitive monitoring of idiosyncratic knowledge has functional utility in causal chains for learning).

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A revised methodology is described for research on metacognitive monitoring, especially judgments of learning (JOLs), to investigate psychological processing that previously has been only hypothetical and unobservable. During data collection a new stage of recall occurs just prior to the JOL, so that during data analysis the items can be partitioned into subcategories to measure the degree of JOL accuracy in ways that are more analytic than was previously possible. A weighted-average combinatorial rule allows the component measures of JOL accuracy to be combined into the usual overall measure of metacognitive accuracy. An example using the revised methodology offers a new explanation for the delayed-JOL effect, in which delayed JOLs are more accurate than immediate JOLs for predicting recall.