Ed Jernigan, Professor and Director of the Centre for Knowledge Integration, will be offering a new course this fall that he has developed.
INTEG 275: Special Topics
Mathematical models in Knowledge Integration: Recognizing patterns across disciplines.
Pattern recognition is a process of detecting, identifying and interpreting structure, order or organization in some context. Mathematics serves as a science of patterns (Keith Devlin) and provides a quantitative framework within which we can understand the nature of patterns, how they behave–and how they are created. The patterns themselves and their mathematical models transcend the disciplines and form the underlying structure of the bridges that realize knowledge integration. Numeracy for knowledge integration implies a facility with quantitative models of natural phenomena and their application to pattern detection, identification, recognition, and interpretation. The purpose of this course is to develop and explore the quantitative description and creation of patterns in time, patterns in space, and patterns in data–to effect knowledge integration across disciplines through the quantitative description of common patterns.