Welcome! I recently completed my Ph.D. in Experimental Psychology at Ohio University with a focus on Cognitive Science. In particular, my research involves understanding behavior related to human categorization and concept learning from empirical, theoretical, and modeling standpoints.
Currently, I am an Assistant Professor of Psychology at Marietta College. This past Fall semester, I taught two sections of Statistics for the Behavioral Sciences (PSYC 285) with their associated laboratories (PSYC 285L) and one section of a graduate-level seminar in Cognitive Psychology (PSYC 611). This Spring semester, I am teaching Introduction to Psychology (PSYC 101), Cognitive Psychology (PSYC 311), and Sensation and Perception (PSYC 394).
MY LATEST PUBLISHED RESEARCH
"On the Learning Difficulty of Visual and Auditory Modal Concepts: Evidence for a Single Processing System" in Cognitive Processing. Conducted two categorization experiments and compared learning behavior for categorical stimuli consisting of visual and auditory dimensions. Discovered identical learning performance regardless of the nature of the stimuli and accounted for the gamut of results utilizing Generalized Invariance Structure Theory.
Abstract: The logic operators (e.g., “and,” “or,” “if, then”) play a fundamental role in concept formation, syntactic construction, semantic expression, and deductive reasoning. In spite of this very general and basic role, there are relatively few studies in the literature that focus on their conceptual nature. In the current investigation, we examine, for the first time, the learning difficulty experienced by observers in classifying members belonging to these primitive “modal concepts” instantiated with sets of acoustic and visual stimuli. We report results from two categorization experiments that suggest the acquisition of acoustic and visual modal concepts is achieved by the same general cognitive mechanism. Additionally, we attempt to account for these results with two models of concept learning difficulty: the generalized invariance structure theory model (Vigo in Cognition 129(1):138–162, 2013, Mathematical principles of human conceptual behavior, Routledge, New York, 2014) and the generalized context model (Nosofsky in J Exp Psychol Learn Mem Cogn 10(1):104–114, 1984, J Exp Psychol 115(1):39–57, 1986).
"Constructing and Deconstructing Concepts: On the Nature of Category Modification and Unsupervised Sorting Behavior" in Experimental Psychology. Investigated the nature of how observers modify multi-dimensional categorical stimuli and linked the results with traditional unsupervised results and procedures. Quantitatively account for one-dimensional, family resemblance, and other types of classification strategies reported in the literature.
Abstract: Several empirical investigations have explored whether observers prefer to sort sets of multidimensional stimuli into groups by employing one-dimensional or family-resemblance strategies. Although one-dimensional sorting strategies have been the prevalent finding for these unsupervised classification paradigms, several researchers have provided evidence that the choice of strategy may depend on the particular demands of the task. To account for this disparity, we propose that observers extract relational patterns from stimulus sets that facilitate the development of optimal classification strategies for relegating category membership. We conducted a novel constrained categorization experiment to empirically test this hypothesis by instructing participants to either add or remove objects from presented categorical stimuli. We employed generalized representational information theory (GRIT; Vigo, 2011b, 2013a, 2014) and its associated formal models to predict and explain how human beings chose to modify these categorical stimuli. Additionally, we compared model performance to predictions made by a leading prototypicality measure in the literature.
"The Structure of Choice" in Cognitive Systems Research. Investigated a fundamental connection between conceptual and choice behavior on multi-dimensional choice sets. Put forth a precise mathematical relationship that accurately accounts for how long observers take to choose their preferred item from the sets.
Abstract: An unsolved fundamental problem in decision science concerns the extent to which the nature of the perceived relationships among items in a set of alternatives influences how they are chosen. More specifically, given a choice set with n items, how does human choice behavior differ as a function of the perceived relationships between the items of the set? In what follows, we study this problem empirically and theoretically from the standpoint of the dimensional structure of the choice set. In particular, we use generalized invariance structure theory (GIST; Vigo, 2013, 2014) to propose an inverse relationship between the degree of concept learning difficulty of a choice set (as determined by its degree of invariance or internal coherence) and choice response times on its members. To our knowledge, this is the first model that precisely unifies these two fundamental constructs. On average, the model, without free parameters, accounts for nearly 90% of the variance in the data from our two response-time experiments.