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What Makes a Good Learner? Neural Evidence for Variation in Encoding

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Knowing how to manage one's own learning has become increasingly important in recent years, as both the need and the opportunities for individuals to learn on their own outside of formal classroom settings have grown. During that same period, however, research on learning, memory, and metacognitive processes has provided evidence that people often have a faulty mental model of how they learn and remember, making them prone to both misassessing and mismanaging their own learning. After a discussion of what learners need to understand in order to become effective stewards of their own learning, we first review research on what people believe about how they learn and then review research on how people's ongoing assessments of their own learning are influenced by current performance and the subjective sense of fluency. We conclude with a discussion of societal assumptions and attitudes that can be counterproductive in terms of individuals becoming maximally effective learners. Expected final online publication date for the Annual Review of Psychology Volume 64 is November 30, 2012. Please see http://www.annualreviews.org/catalog/pubdates.aspx for revised estimates.
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Memory performance in everyday life is often far from perfect and therefore needs to be monitored and controlled by metamemory evaluations, such as judgments of learning (JOLs). JOLs support monitoring for goal-directed modification of learning. Behavioral studies suggested retrieval processes as providing a basis for JOLs. Previous functional imaging research on JOLs found a dissociation between processes underlying memory prediction, located in the medial prefrontal cortex (mPFC), and actual encoding success, located in the medial temporal lobe. However, JOL-specific neural correlates could not be identified unequivocally, since JOLs were given simultaneously with encoding. Here, we aimed to identify the neurocognitive basis of JOLs, i.e., the cognitive processes and neural correlates of JOL, separate from initial encoding. Using functional magnetic resonance imaging (fMRI), we implemented a face-name paired associative design. In general, we found that actual memory success was associated with increased brain activation of the hippocampi bilaterally, whereas predicted memory success was accompanied by increased activation in mPFC, orbital frontal and anterior cingulate cortices. Masking brain activation during predicted memory success with activation during retrieval success revealed BOLD increases of the mPFC. Our findings indicate that JOLs actually incorporate retrieval processes.
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To account for dissociations observed in recognition memory tests, several dual-process models have been proposed that assume that recognition judgments can be based on the recollection of details about previous events or on the assessment of stimulus familiarity. In the current article, these models are examined, along with the methods that have been developed to measure recollection and familiarity. The relevant empirical literature from behavioral, neuropsychological, and neuroimaging studies is then reviewed in order to assess model predictions. Results from a variety of measurement methods, including task-dissociation and process-estimation methods, are found to lead to remarkably consistent conclusions about the nature of recollection and familiarity, particularly when ceiling effects are avoided. For example, recollection is found to be more sensitive than familiarity to response speeding, division of attention, generation, semantic encoding, the effects of aging, and the amnestic effects of benzodiazepines, but it is less sensitive than familiarity to shifts in response criterion, fluency manipulations, forgetting over short retention intervals, and some perceptual manipulations. Moreover, neuropsychological and neuroimaging results indicate that the two processes rely on partially distinct neural substrates and provide support for models that assume that recollection relies on the hippocampus and prefrontal cortex, whereas familiarity relies on regions surrounding the hippocampus. Double dissociations produced by experimental manipulations at time of test indicate that the two processes are independent at retrieval, and single dissociations produced by study manipulations indicate that they are partially independent during encoding. Recollection is similar but not identical to free recall, whereas familiarity is similar to conceptual implicit memory, but is dissociable from perceptual implicit memory. Finally, the results indicate that recollection reflects a thresholdlike retrieval process that supports novel learning, whereas familiarity reflects a signal-detection process that can support novel learning only under certain conditions. The results verify a number of model predictions and prove useful in resolving several theoretical disagreements.
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Separate event-related brain potential (ERP) components have been hypothesized to index familiarity and recollection processes that support recognition memory. A 300- to 500-ms mid-frontal FN400 old/new difference has been related to familiarity, whereas a 500- to 800-ms parietal old/new difference has been related to recollection. Other recent work has cast doubt on the FN400 familiarity hypothesis, especially its application to familiarity-based recognition of conceptually impoverished stimuli such as novel faces. Here we show that FN400 old/new differences can be observed with novel faces, and as predicted by the familiarity hypothesis, these differences are observed regardless of whether or not recognition is accompanied by the recollection of specific details from the study episode. Furthermore, FN400 differentiation between hits and misses is more consistent with an explicit familiarity process than an implicit memory process.