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Description: Metamemory, or the ability to understand the capacities of one’s own memory, is important for learning. A common method for assessing metamemory is the Judgment of Learning (JOL) task in which participants are asked to judge the likelihood of correctly remembering a target word in a cue-target word pair when only presented with the cue at test. The associative direction of the cue-target pair can affect JOL accuracy. Unlike forward pairs (e.g., credit-card), in which JOLs accurately predict recall, an illusion of competence has been reported for backward associates (e.g., card-credit), symmetrical associates (e.g., salt-pepper), and unrelated pairs (e.g., artery-bronze) in which JOLs overestimate later recall. The present study evaluates whether the illusion of competence can be reduced when participants use a deep item-specific or relational encoding strategy relative to reading. Overall, item-specific and relational encoding were found to reduce the illusion of competence for backward and unrelated pairs while improving the calibration between JOLs and recall. However, these encoding strategies largely reduced resolution, except for when pairs were unrelated. Thus, item-specific and relational encoding strategies are effective at reducing the illusion of competence by improving JOL calibration but not resolution.