Dr. Richard Jagacinski

Dr. Richard  Jagacinski

Dr. Richard Jagacinski

Professor, Cognitive


(614) 292-1870

208 Lazenby Hall
1827 Neil Avenue
Columbus, OH

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  • Bachelor's Degree: Electrical Engineering, Princeton University
  • Ph.D.: Experimental Psychology, The University of Michigan

My research explores rhythmic attention in athletic and musical performance (e.g., golf, drumming), attention and memory in vehicular control, perceptual-motor skills in older adults, and creative behavior. (Click on Professional Website for details.) My teaching explores parallels between models of decision making and movement control in dynamic contexts, perceptual-motor control and learning, the behavioral impacts of technology on quality of life, and research methods.

Courses Taught

Psychology 5309 -- Human Motor Control and Learning

This course examines the processes underlying the performance, learning, and adaptation of movement skills such as walking, running, driving, drumming, catching, golfing, text editing, and social communication. Motion skills are often sophisticated in their behavioral organization and reflect implicit problem solving in coordinating multiple limbs and meeting environmental demands. Motion patterns can also be used to make inferences about underlying cognitive processes such as selective perception, attention, and memory in the context of action. Analyzing motion is therefore an important aspect of understanding human behavior. Graduate and upper level undergraduate students from all departments are welcome.

Psychology 5620 -- Technology, Efficiency, and Happiness

This course examines various ways of evaluating behavioral aspects of new technologies (e.g., social media, artificial intelligence chatbots, mobile communication devices, transportation innovations).  Many new products seem like they might improve our lives through increased efficiency, convenience, or power in performing specific tasks.  However, it is difficult to predict whether new technology will make us happier or kinder, enhance social interactions, increase creativity, or generally improve our quality of life.   Technology often has hidden costs and benefits such as unexpected effects on cultural manners, new forms of distributed cognition and social cooperation, increased multi-tasking, destabilizing environmental impacts, greater expectations for speeded performance, and displacement of some occupations.  This course considers many behavioral dimensions of technology that may impact decisions about designing, deploying, and incorporating new devices into our lives.  Graduate and upper level undergraduate students from all departments are welcome.

Psychology 7816 – Action and Decision Making

Decision making and/or movement patterns in activities such as driving, flying, resource management, administrative policy adjustment, and health care involve dynamic interactions between people, technology, and their environments over extended periods of time.  This course will explore behavioral aspects of control theory, a set of mathematical tools for analyzing and influencing the trajectories of such complex systems.  

Analysis of system dynamics can reveal spatio-temporal aspects of perception, attention, memory, and cue utilization.  Students will become familiar with elementary dynamic systems such as negative feedback systems that diminish deviations from a desired goal, positive feedback systems that amplify small deviations, and the interesting interplay of these two types of dynamics in complex behaviors, e.g., the epidemic-like adoption of new technology.  These concepts can be used to model a broad range of behavioral phenomena such as speed-accuracy tradeoffs in movement, car drivers’ attentional distributions, temporal discounting of the past and future, misunderstandings of climate dynamics, and growth, decline, and tipping points in group decision making.  Graduate students from all departments are welcome.  Advanced undergraduates can obtain permission from the instructor.


Selected Publications

Liao, M., Jagacinski, R. J., & Greenberg, N. (1997). Quantifying the performance limitations of older and younger adults in a target acquisition task. Journal of Experimental Psychology: Human Perception and Performance, 23, 1644-1664.

Jagacinski, R. J., Peper, C. E., & Beek, P. J. (2000). Dynamic, stochastic, and topological aspects of polyrhythmic performance. Journal of Motor Behavior, 32, 323-336.

Jagacinski, R. J. & Flach, J. M. (2003). Control theory for humans: Quantitative approaches to modeling performance. Mahwah, New Jersey: Erlbaum.

Jagacinski, R. J. (2010). A geometrical view of the Crucifix: A call to novel acts of kindness. Parabola, 35(4), 100-103.

Kim, T., Jagacinski, R. J., & Lavender, S. A. (2011). Age-related differences in the coordinative structure of the golf swing. Journal of Motor Behavior, 43, 433-444.

Klapp, S. T. & Jagacinski, R. J. (2011). Gestalt principles in the control of motor action. Psychological Bulletin, 137, 443-462.

Charyton, C., Holden, J. G., Jagacinski, R. J., & Elliott, J. O. (2012). A historical and fractal perspective on the life and saxophone solos of John Coltrane. Jazz Perspectives, 6(3), 311-335.

Jagacinski, R. J., Rizzi,E., Kim, T., Lavender, S. A., Speller, L. F., & Klapp, S. T. (2016). Parallel streams vs. integrated timing in multi-limb pattern generation: A test of Korte’s Third Law. Journal of Experimental Psychology: Human Perception and Performance, 42, 1703-1715.

Jagacinski, R. J., Rizzi, E., Bloom, B. J., Turkkan, O. A., Morrison, T. N., Su, H., & Wang, J.  (2019). Drivers’ attentional instability on a winding roadway. IEEE Transactions on Human-Machine Systems, 49(6), 498-507.

Morrison, T. N., Jagacinski, R. J., & Petrov, J. (2023). Drivers’ attention to preview and its momentary persistence.  IEEE Transactions on Human-Machine Systems, 53(3), 610-618.