A model for the economic evaluation of training alternatives for complex logging tasks Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/9k41zh33h

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  • Training of woodsworkers is described as important for the logging industry in Oregon. There has been little documentation of training gains or research that measures the effects of training from the perspective of the logging firm. Learning theories are evaluated and Towill's form of learning curves are selected for an experiment. A decision model is developed to assess the training gains in complex chokersetting tasks. Thirty subjects are matched and split into a control and experimental group based on initial task performance. Designed training is provided to the experimental group while the control group learns the way industry commonly performs training. Results are presented after six weeks of the experiment. Training gains are significant -- eighteen percent time savings in favor of the experimental group. Other statistical results were suggested by learning theory. Results of the experiment are incorporated and translated into the decision model developed. A simplified approach is described for logging firms. Simulation and sensitivity analysis are used to examine parameters of interest which include training gains, training costs, job change characteristics of workers, and recovery points of training costs. Summary discussions identify implementation obstacles and future research needs.
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  • description.provenance : Made available in DSpace on 2008-10-10T18:11:04Z (GMT). No. of bitstreams: 1 Garland, John PhD.pdf: 1076896 bytes, checksum: 2d372052bba6db51a6d8719e336e9d75 (MD5)
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  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2008-10-10T18:06:48Z (GMT) No. of bitstreams: 1 Garland, John PhD.pdf: 1076896 bytes, checksum: 2d372052bba6db51a6d8719e336e9d75 (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2008-10-10T18:11:03Z (GMT) No. of bitstreams: 1 Garland, John PhD.pdf: 1076896 bytes, checksum: 2d372052bba6db51a6d8719e336e9d75 (MD5)

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