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Generalizability of Manual Control Skills Between Control Tasks of Varying DifficultyThis paper presents the results of an experiment that was performed at NASA Ames Research Center using 18 participants in two different groups who trained a task for ten days, with the goal of identifying how skill generalization would occur between two similar tasks of varying difficulty. A cybernetic approach was used. The first group was trained in a simple one-dimensional tracking task and transferred to a difficult two-dimensional tracking task. For the second group, this was reversed. Training with a simple task before transferring to the difficult task resulted in a slower convergence to final performance. However, it did allow participants to start with a better initial performance in the difficult task. Furthermore, after training with a simple task, participants controlled with a higher gain and generated lower lead time constants. However, possibly due to the number of participants, this experiment did not find any statistical evidence to support the conclusion that training with a simple task version helps in learning a more complex task.
Document ID
20190030843
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Pieters, Marc A.
(San Jose State Univ. Moffett Field, CA, United States)
Zaal, Peter M. T.
(San Jose State Univ. Moffett Field, CA, United States)
Date Acquired
September 18, 2019
Publication Date
September 16, 2019
Subject Category
Behavioral Sciences
Report/Patent Number
ARC-E-DAA-TN69286
Report Number: ARC-E-DAA-TN69286
Meeting Information
Meeting: IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design, and Evaluation of Human-Machine Systems (HMS 2019)
Location: Tallinn
Country: Estonia
Start Date: September 16, 2019
End Date: September 19, 2019
Sponsors: International Federation of Automatic Control
Funding Number(s)
CONTRACT_GRANT: NNX17AE07A
CONTRACT_GRANT: NNX12AB08A
Distribution Limits
Public
Copyright
Public Use Permitted.
Technical Review
NASA Technical Management
Keywords
skill generalizability
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