Citation

So JC, Proctor RW, Dunston PS, Wang X. Hum. Factors 2013; 55(2): 449-460.

Affiliation

School of Industrial Engineering, Purdue University, 315 N. Grant St., West Lafayette, IN 47907, USA. soc@purdue.edu

Copyright

(Copyright © 2013, Human Factors and Ergonomics Society, Publisher SAGE Publishing)

DOI

unavailable

PMID

23691837

Abstract

OBJECTIVE: We examined whether part-task training produces better learning and retention than whole-task training of a trench-and-load task performed on a hydraulic excavator simulator. BACKGROUND: For complex perceptual-motor tasks that involve several components and require spatial awareness of the environment, part-task training will be effective if the benefit of being able to focus attention on each component outweighs the cost of integrating the components. We predicted that such would be the case for learning to operate an excavator. METHOD: A part-task training group practiced separate Carrier Positioning, Trenching, and Truck Loading modules, whereas a whole-task training group practiced the Trench and Load module, which combines elements from the other modules. The latter module, involving different scenarios, was performed by both groups immediately after training and following a 2-week retention interval. RESULTS: Production rate on the trench-and-load task was better overall on the retention test than on the immediate test. The part-task group showed improvement on the retention test compared with the immediate test, whereas the whole-task group did not. The part-task group showed higher productivity rates than did the whole-task group on the retention test. CONCLUSION: Part-task training on the excavator simulator results in better skill retention than does whole-task training. The benefit of part-task training is likely to be found for other tasks requiring control of implements in various environments. APPLICATION: Part-task training can result in better retention of complex perceptual-motor skills involving several components, even when immediate transfer to the whole task does not show better performance than whole-task training.

Language: en