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Zhao, Wenbo; Yin, Yue; Hu, Xiao; Shanks, David R.; Yang, Chunliang; Luo, Liang – Metacognition and Learning, 2023
Item memory (e.g., recall or recognition of specific items) can reactively change when metacognitively monitored via judgments of learning (JOLs). The current research explores whether memory for inter-item relations (e.g., semantic relations among list items) is reactively influenced by JOLs. Participants in Experiment 1 studied rhyming word…
Descriptors: Memory, Metacognition, Recall (Psychology), Learning
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Chang, Minyu; Brainerd, C. J. – Metacognition and Learning, 2023
Making judgments of learning (JOLs) can sometimes modify subsequent memory performance, which is referred to as JOL reactivity. We evaluated two major theoretical explanations of JOL reactivity and used the dual-retrieval model to pinpoint the retrieval processes that are modified by JOLs. The changed-goal hypothesis assumes that JOLs highlight…
Descriptors: Cues, Evaluative Thinking, Models, Recall (Psychology)
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Hawkins, Robert D.; Kandel, Eric R. – Learning & Memory, 2019
One of the major questions in psychology is whether associative and nonassociative learning are fundamentally different or whether they involve similar processes and mechanisms. We have addressed this question by comparing mechanisms of a nonassociative form of learning, sensitization, and an associative form of learning, classical conditioning of…
Descriptors: Associative Learning, Classical Conditioning, Brain, Animals
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Lew, Timothy F.; Pashler, Harold E.; Vul, Edward – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
What happens to memories as we forget? They might gradually lose fidelity, lose their associations (and thus be retrieved in response to the incorrect cues), or be completely lost. Typical long-term memory studies assess memory as a binary outcome (correct/incorrect), and cannot distinguish these different kinds of forgetting. Here we assess…
Descriptors: Experimental Psychology, Long Term Memory, Learning, Visual Stimuli
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Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E. – Learning & Memory, 2016
Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…
Descriptors: Learning, Cognitive Processes, Animals, Error Patterns