Date of Award
Master of Science (MS)
Computational and Data Sciences
Older adults (OAs) typically experience memory failures as they age. However, with some exceptions, studies of OAs’ ability to assess their own memory functions– Metamemory (MM)– find little evidence that this function is susceptible to age-related decline. Our study examines OAs’ and young adults’ (YAs) MM performance and strategy use. Groups of YAs (N = 138) and OAs (N = 79) performed a MM task that required participants to place bets on how likely they were to remember words in a list. Our analytical approach includes hierarchical clustering, and we introduce a new measure of MM—the modified Brier—in order to adjust for di↵erences in scale usage between participants. Our data indicate that OAs and YAs di↵er in the strategies they use to assess their memory and in how well their MM matches with memory performance. However, there was no evidence that the chosen strategies were associated with di↵erences in MM match, indicating that there are multiple strategies that might be e↵ective (i.e. lead to similar match) in this MM task.
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Parlett, Chelsea, "Exploring Age-Related Metamemory Differences Using Modified Brier Scores and Hierarchical Clustering" (2019). Computational and Data Sciences (MS) Theses. 3.