Applications of Computational Matrix Algebra PROCEEDING
Gerard Rambally, University of North Texas at Dallas, United States
Society for Information Technology & Teacher Education International Conference, in Austin, TX, United States ISBN 978-1-939797-27-8 Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
Many researchers have put forward convincing arguments that mathematical thinking (MT) plays a crucial role in computational thinking (CT). MT and CT share several modes of thought, particularly in representation of reality, reduction to simpler problems, abstract reasoning, information structures, and algorithms. MT directly translates into thinking recursively, iteratively, abstractly, logically, precisely, and procedurally. Through these experiences students explicitly learn a number of critical CT principles and more importantly, develop a cognitive model for computational phenomena. This paper focuses on the integration of CT skills in secondary school mathematics and in the general education university curriculum. Using example concepts from matrix algebra, this paper demonstrates how key CT skills including algorithmic thinking, problem reformulation via problem transformation, problem reduction, and problem representation, can be fostered without computer programming.
Rambally, G. (2017). Applications of Computational Matrix Algebra. In P. Resta & S. Smith (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2017 (pp. 72-79). Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).
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