Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s41039-018-0071-2 | Research and Practice in Technology Enhanced Learning |
Keywords | Field | DocType |
Big data management skills, Digital skills development, Cognitive performance measurement, Instructional design, Human-computer interaction, Item response theory, Rasch model | Educational technology,Corporate governance,Computer science,Knowledge management,Dreyfus model of skill acquisition,Item response theory,Instructional design,Big data,Rasch model,Comprehension | Journal |
Volume | Issue | ISSN |
13 | 1 | 1793-7078 |
Citations | PageRank | References |
1 | 0.63 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elspeth McKay | 1 | 9 | 8.19 |
| Marlina Mohamad | 2 | 1 | 1.30 |