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Teaching innovation in an age of disruption
Author(s) -
Kresta Suzanne M.
Publication year - 2021
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.24133
Subject(s) - mindset , curiosity , computer science , obligation , context (archaeology) , engineering ethics , engineering management , knowledge management , engineering , psychology , political science , artificial intelligence , social psychology , paleontology , law , biology
In a climate of global disruptions, it seems certain that adaptive change will be an important part of our lives for the foreseeable future. Now, more than ever, we have a responsibility to introduce our students to skills that will support them in this work. This paper is a synthesis of a number of invited plenary talks given from 2014–2019 which explore the dichotomy of engineering: we are innovators and problem solvers who also hold reliability and protection of the public as our most important obligation. The data show that innovation will become more important in the decades ahead, but finding academics who love the uncertainty that comes with teaching design is becoming more difficult. The tension—and occasional polarization—between prioritizing innovation or maintaining reliable known solutions is deconstructed and explored. Two examples of how this plays out in industry are presented. The second half of the paper presents a selection of important ideas for teaching innovation thinking. Practical teaching strategies are included for easy implementation in the classroom. In closing, the major threads in (engineering) teaching and learning research are summarized, again, with samples of best practices in the context of teaching collaborative innovation. The goal of this paper is to provide engineering instructors with tools which are easily applied to build curiosity and an innovation mindset, without reducing their commitment to reliable and robust engineering problem solving.