Date of Award
May 2023
Degree Type
Thesis
Degree Name
Master of Science
Department
Psychology
First Advisor
Caitlin R Bowman
Committee Members
Karyn M Frick, Deborah E Hannula
Keywords
affect, category learning, cognitive aging, mood, motivation, state of mind
Abstract
Category learning plays an important role in day-to-day lives across all ages, allowing us to organize related experiences, develop expectations, and determine how we behave given those expectations. Despite its importance, the current body of literature on category learning in older adults is much smaller than that of other memory domains. Thus, little is known about how well older adults learn new concepts and what factors best promote learning novel categories. One factor that may affect category learning abilities is an individual’s state of mind. A number of studies demonstrate the effects of sleep, stress, affect, and motivation on cognition, especially in older adults. However, the extent to which individual’s state of mind affects category learning remains unclear. In this study, older adults have undergone two category learning sessions across separate days and completed several state of mind questionnaires. I examined if participant’s state of mind predicted the categorization accuracy of older adults on each day. This study may potentially advance our understanding of the factors that influence category learning and establish the extent to which state of mind contributes to older adults’ categorization abilities.
Recommended Citation
Kimura, Kana, "Does State of Mind Predict Prototype-based Category Learning in Older Adults?" (2023). Theses and Dissertations. 3171.
https://dc.uwm.edu/etd/3171
Included in
Cognitive Psychology Commons, Neuroscience and Neurobiology Commons, Other Medicine and Health Sciences Commons