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Effect of Data Science Teaching for Non-STEM Students. A Systematic Literature Review

Authors:
Luiz Barboza
Erico Teixeira

Keywords: Data Science; Non-STEM; Teaching.

Abstract:
The evolution of computing capacity allowed specialists in certain areas to benefit from this advance, although with little knowledge about data analysis technologies. In this way, our role as software scientists, more than increasing computational power, is to facilitate the access of people from other areas to these technologies and, with this combined effort, bring more relevant results to society. With this objective in mind, a systematic literature review was carried out to understand if (RQ1), how (RQ3) and why (RQ2) data science is being taught to students of non-STEM (Science, Technology, Engineering and Mathematics). The bases used in this research were ACM and IEEE, dismissing the articles that met the exclusion criteria. These criteria were: a) articles focused on the use of technology to improve the learning process in general; b) articles targeting different groups than the one prioritized here, non-STEM; c) educational improvements obtained with different proposals other than the introduction of data science.

Pages: 118 to 122

Copyright: Copyright (c) IARIA, 2020

Publication date: October 18, 2020

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-827-3

Location: Porto, Portugal

Dates: from October 18, 2020 to October 22, 2020