Metamemory

Metamemory is a subdiscipline of the study of metacognition—those processes involved in monitoring (assessing) cognition so as to modify and control behavior. Accordingly, research in metamemory is concerned with how individuals monitor and control learning and memory. Although thinking and writing about memory dates back to the ancient Greeks, formal scientific study of metamemory is a comparatively young endeavor that started to gain impetus in the 1960s. Much of the earliest work was concerned with children’s understanding of memory. Research on children’s metamemory has continued unabated, but mainstream cognitive psychologists became increasingly interested in metacognitive processes in the 1980s, with a steady increase in the volume of work on metamemory since that time. Modern research in metamemory is guided by a fundamental assumption that one’s understanding of one’s own memory guides behavior. For example, a student who believes that he or she has fully mastered the content covered by an upcoming exam may cease further study. Given the presumption of a strong relationship between monitoring and self-regulation (control) of learning, researchers have focused on the accuracy of metamemory and proposed a number of accounts of judgment. Such theories have been informed by a diversity of methodological approaches and measures, many of which reflect the specific memory process being studied. Findings from research on metamemory have significant implications for theoretical approaches to learning and understanding of consciousness and self-regulation. They also have applications in a variety of field settings, such as within education and eyewitness memory. Recent developments have sought to better situate research in metamemory within such applied contexts and to consider more complex experimental and statistical models of metamemory to better understand how multiple sources of information are integrated to inform judgment. These developments underscore a central theme in the field, as new theoretical approaches are driven by refinements in methodology and measurement.