Bayesian Modeling and Dissipative Structures Theory: Complementary Methods for Exploring Complexity

• In Event: Moscone Center North Roundtable Session 5
  In Roundtable Session: Perspectives on Complexity in Education

Abstract

This research relies primarily on the works of Prigogine (1967, 1980, 1996) on dissipative structures theory as a lens for understanding Bayesian modeling and its implications for complexity theory. For the purposes of this paper, I draw primarily from Levy and Mislevy’s (2016) research on Bayesian modeling. As a result, since Bayesian inference relies on conditional probabilities, or those that are conditional to both internal and external systemic factors, its focus is not on causality. The purpose of this paper, therefore, is to investigate Bayesian modeling as a quantitative approach to complexity theory and dissipative systems in educational research.

Author

• Donald L. Gilstrap, The University of Alabama