A Model to Pedagogically Support Teaching & Learning Scenarios For Engineering Innovation from a Complexity Sciences Perspective

Abstract

Education for innovation requires innovation in education. To innovate in education implies new pedagogical models. It is not enough to just apply teaching/learning methods or strategies in a mechanical or procedural approach. It requires the conception of new pedagogical models based on theories that allow for processing of different interpretations of diverse complexity educational phenomena, i.e. other ways of producing and implementing pedagogical knowledge. Education in the different engineering programs has been carried out through analytical and linear processes; however, the reality of education through a Complex Systems lens is characterized by uncertainty, chaos, breaks, nonlinearity and self-organization. To optimize curriculum processes that foster innovation skills in students requires strategies and teaching-learning scenarios that stimulate nonlinear processes and generate a change in the mindset of the professor and the student. It is important to understand and approach the reality of educating engineers in new ways. Making methodological adjustments without the understanding of the epistemological orientation that take into account complex dynamic processes will only generate pseudo-changes, which limits creativity and innovation processes. Currently, there are several global initiatives for the development of teaching-learning scenarios that facilitate innovation processes in engineering education and education for innovation. This paper is a proposal by the Complex Systems & Education Network (SCED-ISTEC) and the College of Engineering at the University of South Florida (USF), of a model developed to pedagogically support innovation scenarios in educating engineers for innovation using the principles of Complex Systems. The suggested scenarios are framed in a dynamic curriculum structure. They are characterized by hard and soft state-of-the-art technologies; interdisciplinary, flexible, pedagogical research processes; methodologies for cognitive restructuring, solving complex problems, and modeling, simulation; interactions with university/industry programs; and the facilitating of applications according to context and societal needs.