Abstract
Data from 15 jewellery students, in their 1st and 3rd years of training, are analysed. Participants were asked to use a piercing saw to cut 5 lines in a piece of metal. Data from strain gauges and a tri-axial accelerometer (built into the handle of the saw) were recorded and thirteen measures of performance derived from these data. The measures were categorised in terms of control, regulatory and functional parameters. Principal Components Analysis defined five components: sawing action; grasp of handle; task completion; quality of lines cut. Participants were classed, on the basis of their data, in terms of ‘high’, ‘medium’ and ‘low’ expertise. Non-parametric statistical analysis revealed significant differences between the classes of expertise on control, regulatory and functional parameters. While ‘expertise’ was directly related to year of study, the results demonstrate that participants with ‘high’ expertise tended to produce better quality lines, to use less grip force and to use more of the blade when cutting. This shows how data collected from work settings can be used to define skill level in practitioners.
Original language | English |
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Pages (from-to) | 211-221 |
Journal | Applied Ergonomics |
Volume | 51 |
Early online date | 6 Jun 2015 |
DOIs | |
Publication status | E-pub ahead of print - 6 Jun 2015 |