Big data management skills: accurate measurement

McKay, E and Mohamad, M 2018, 'Big data management skills: accurate measurement', Research and Practice in Technology Enhanced Learning, vol. 13, no. 5, pp. 1-24.


Document type: Journal Article
Collection: Journal Articles

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Title Big data management skills: accurate measurement
Author(s) McKay, E
Mohamad, M
Year 2018
Journal name Research and Practice in Technology Enhanced Learning
Volume number 13
Issue number 5
Start page 1
End page 24
Total pages 24
Publisher SpringerOpen
Abstract Some say that big data is transforming business and society. This can mean wide-reaching disruption for commerce, health and world governance. Few authors agree on what constitutes big data, depending on the philosophical stance taken. Our propensity for keeping data archived is posing major issues globally, with retrieval and application of such data crossing ethical boundaries. However, one of the more pressing issues is the growing need for confirming whether those working with such big data have the required digital skills to cope. This paper presents one effective and efficient way to identify such digital skill acquisition. We show the progression from the earlier approach used for measuring proficiency between novice and experienced programmers using traditional statistical measures, to adopting a more comprehensive unidimensional scale that empowers comprehension of human performance and test-item performance relative to each other. This methodology offers an effective tool for understanding of individual differences in digital skill development.
Subject Computer-Human Interaction
Information Systems Theory
Education Assessment and Evaluation
Keyword(s) Big data management skills
Digital skills development
Cognitive performance measurement
Instructional design
Human-computer interaction
Item response theory
Rasch model
DOI - identifier 10.1186/s41039-018-0071-2
Copyright notice © The Author(s). 2018, corrected publication June/2018. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
ISSN 1793-7078
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