A Data Science Enhanced Framework for Applied and Computational Math

Samuel Sambasivam, Kirby McMaster, Brian Rague, Stuart L Wolthuis
InSITE 2018  •  2018  •  pp. 913
[This Proceedings paper was revised and published in the 2018 issue of the journal Issues in Informing Science and Information Technology, Volume 15]

The primary objective of this research was to build an enhanced framework for Applied and Computational Math. This framework allows a variety of applied math concepts to be organized into a meaningful whole. The framework can help students grasp new mathematical applications by comparing them to a common reference model. In this research, we measured the most frequent words used in a sample of Math and Computer Science books. We integrated these words with those obtained in an earlier study, from which we had constructed the original Computational Math scale. The enhanced framework improves our Computational Math scale by integrating selected concepts from the field of Data Science. The resulting enhanced framework better explains how abstract mathematical models and algorithms are tied to real world applications and computer implementations.
Framework, Applied Math, Computational Math, Data Science, concordance.
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