Here you’ll find a list of current Graduate course offerings on the Storrs campus. For detailed course information, clicking on the class title will open a new tab.
Fall 2023
AH5200: Design & Methodology of Behavioral Trials (3 credits)
Mondays 2PM-4:30PM, Gentry 232
Instructor: Sherry Pagoto, sherry.pagoto@uconn.edu
Description: This course is intended for graduate students in the health and behavioral sciences, public health or related field AND advanced undergraduate students who are graduate school bound. Preventable diseases, including cardiovascular disease, diabetes and cancer, are the top causes of morbidity and mortality in the US. All are linked to lifestyle behaviors. Behavioral interventions can improve physical and/or mental health using behavioral, social, educational, and cognitive strategies. Randomized trials testing behavioral interventions have unique methodological challenges relative to drug and device trials. This course will cover methodological issues pertinent to behavioral trials including pilot feasibility trials, efficacy trials, effectiveness trials, implementation trials, and dissemination trials. Methodological issues discussed include randomization, control group selection, internal and external validity, treatment receipt and fidelity, adherence, recruitment, intent to treat, and blinding. Students will learn how to design scientifically sound behavioral intervention trials as well as how to critically evaluate behavioral trials published in the literature.
COGS 5001: Cognitive Science Proseminar (1-3 credits)
Thursdays 2PM-4PM, Arjona 307
Instructor: Dr. Dimitris Xygalatas, dimitris.xygalatas@uconn.edu
Description: Cognitive Science is the interdisciplinary study of cognition which includes research within several disciplines including, but not limited to psychology, linguistics, speech, language and hearing sciences, philosophy, computer science, anthropology, neuroscience, English, mathematics, law, and economics. This proseminar provides an in-depth examination of current research in the cognitive sciences. Each week, we will have a specialized presentation by a different Cognitive Science faculty affiliate at the University of Connecticut, with speakers coming from a wide range of departments across campus. The course aims to provide: an introduction to cognitive science research at the University of Connecticut a representative sample of questions, concepts and research methods in different disciplines practice as an academic by finding and consuming research articles, asking questions in front of an audience, formulating research ideas and giving oral presentations to a diverse audience.
PSYC 5553: Introduction to Nonlinear Dynamics (3 credits)
Mondays 1:25PM-4:25PM, Bousfield 394
Instructor: Edward Large, edward.large@uconn.edu
Description: This course aims to provide an introduction to nonlinear dynamical systems, the type of mathematics that is used to model physical, biological, psychological, and engineered systems including fireflies, neurons, networks, human perception-action, robotics, and social systems. It introduces students to the major concepts of dynamical systems, including state space, stability, and bifurcation theory. Emphasis is on exploration of systems via computer simulation and mathematical analysis. Familiarity with algebra and the calculus is assumed, but all needed techniques will be reviewed during the course.
In the first semester, you will learn the mathematics, beginning with simple systems, and ultimately arriving at some pretty complicated ones. We use “Nonlinear Dynamics and Chaos” by Strogatz. Students will also receive instruction in basic Matlab programming. There is also an optional second semester, in which each student will apply what was learned in the first semester to a modeling project related to their own research.
Our goal will be to make it through Chapter 8 of the textbook. Depending on the our progress, we may make it to some more advanced topics, such as Chaos. Mastery of this material will put the student in an excellent position to create and understand dynamical systems models of real phenomena of current interest in physiology, biology, engineering, neuroscience, and psychology, and to read and understand models published in the literature.
Fridays 9AM-12PM, Bousfield A106
Instructor: James Magnuson, james.magnuson@uconn.edu
Description: This class is a hands-on introduction to several kinds of computational models used in the cognitive and neural sciences. In science, computational models are tools we use to test and refine theories. No programming background is required. Students will learn programming basics so that they can work with already-implemented models (and students can choose to do more advanced challenges). The modeling and programming we cover could help prepare students for advanced studies in various disciplines, and/or a foundation for delving more deeply into machine learning or data science. Students should bring a laptop to class each week.