I am a doctoral student of Psychology at Georgia Tech, where I am a part of the Adult Cognition Lab (ACL). My research, which uses both behavioral and modeling techniques, focuses on how memory and memory decisions change with age.
When we think about aging, we commonly hark upon declines in declarative episodic memory, specifically in explicit recall. While it is true that normally-aging older adults have greater difficulty with explicit recall than do younger adults, they are still able to provide accurate decisions about their memory that allow them to function normally in their daily lives. With Dr. Chris Hertzog and the Adult Cognition Lab (ACL), I study the accuracy of memory judgments across the lifespan and the strategies that can aid individuals in making decisions about their own knowledge, even when specific information cannot be directly recalled. Recently, we have been examining feelings-of-knowing (FOKs), which scale confidence that an individual will be able to recognize an item that they cannot currently recall and, in turn, allows researchers to make inferences about that individual's access to diagnostic information in the absense of explicit memory.
A major focus of the research that I conducted as an undergraduate at UNCW as well as a master's student at Villanova, and continue to research at Georgia Tech, is on understanding metacognitive monitoring (monitoring the status of the cognitive system) during experimental tasks. Specifically, how well can individuals judge their current level of knowing of to-be-remembered information? How accurate are their predictions of remembering that information in the future? With the Adult Cognition Lab, I use predictive judgments of if an item will be recognized in the event that it cannot be recalled (called feeling-of-knowing [FOK] judgments) to assess metacognitive accuracy in both young and older adults.
Although they largely escape our awareness, we use metacognitive monitoring constantly during learning to determine how to study information that needs to be remembered at a later time as well as how much time we should spend studying that information. A large focus of my research on the relationship between monitoring and control is on the decisions that learners make during studying when introduced to certain task manipulations, such as the difficulty of the items being studied or the wording of the instructions that are presented before learning even begins. Much of my research with Dr. Toppino at Villanova was concerned with these issues, although we are continuing to explore how utilization of monitoring differs across the lifespan at Georgia Tech.
Research in cognitive psychology indicates that individuals do not have direct (or "privileged") access to the contents of their own memory. Cues diagnostic of information of interest, however, are available, though these cues may or may not be accessible at the time of inference. Furthermore, inferential cues can be overwhelmed by cues that are not diagnostic of a true memory state, such as fluency of retrieval or item associativeness. In order to understand this "multiple-cue utilization" (MCU) hypothesis of metacognition, the ACL, along with Dr. Rick Thomas and David Illingworth of the Decision Processes Lab (DPL), are modifying an existing cognitive architecture (MINERVA) to model how memory decisions are made based on the integration of multiple memory cues.
Infants face great acoustic developmental challenges - not only must they learn to distinguish speech tokens (i.e., individual vowel and consonant sounds), but they must do so while encountering high variability in these tokens between speakers. A large source of speaker invariance, for example, comes from differences between genders, with female speaker tokens registering at higher levels on the acoustic spectrum than male speakers. Despite this lack of invariance, infants readily learn differences between vowel sounds through observing their stochastic properties. Led by Dr. Joe Toscano at Villanova University, we are developing a computational model of vowel category learning in infants that both capitalizes on statistical learning and accounts for speaker variability.
Predicting how soldiers will perform on the battlefield is imperative to preditive military tactics. What is relatively uncertain, however, is how constellations of moderating varibles, such as fatigue and stress, impact larger cognitive and physical systems. During my time as an intern at Charles River Analytics, I helped research and develop intelligent software to help answer these questions in realistic simulations of individual soldiers.
Advisor: Chris Hertzog, PhD
Adult Cognition Lab (ACL)
Thesis Advisor: Thomas Toppino, PhD
Memory and Cognition Lab
Word Recognition and Auditory Perception (WRAP) Lab
Thesis Advisor: Jeffrey Toth, PhD
Aging and Cognitive Training (ACT) Lab
When I am not working on my graduate studies, I enjoy spending my free time outside playing tennis. You can often find me playing tennis at Piedmont Park here in Atlanta in a 4.0 singles flex league or with my ALTA doubles team. I also enjoy hiking in the Appalachian Mountains when the weather is nice.
In the rare moments in which I'm neither working nor playing tennis, I enjoy reading, learning about new data analysis/programming technologies, watching Netflix, and (unsuccessfully) modifying simple robots.