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Examining connectivity across the two training domains provided a distinctive comparative insight to elucidate the robustness of any effects.
More broadly, we posit that this method can be used for additional complex training domains that require cognitive, perceptual and psychomotor skills and knowledge such as maintenance tasks.
This method provides a novel approach to task analyses across complex training domains, and particularly for medical training tasks which exercise complex integrated skills.
Training domains such as RALS require an extension of the task modeling techniques employed in cognitive domains such as problem-solving in order to also model the skills exercised in perceptual and psychomotor domains within the underlying ITS framework.
However, such methods often fail when presented with a novel domain, and a series of works have shown that when classifiers are evaluated outside of their training domains, the performance degrades significantly [7, 8].
Research findings in the business-related vocational training domains regarding the impact of ESCS are limited: there is only the study by Kotte and Lietz (1998), who found that the parents' highest level of education is one of the most important predictors.
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Predictive BNs are generalisations of a system that have skill at predicting outside of the training domain.
A priori evaluation of the ANN generality within and outside its training domain is carried out using stand-alone LEM simulations as well.
Second, we perform two multilevel multigroup comparisons to test the potentially moderating effects of the categorical variables training type and training domain (i.e., occupational field).
To test assumed emotional crossover and to investigate potential moderation by training type and training domain, we specified the models presented in Fig. 1.
The results demonstrate that with on-line adaptation of weights, it is possible to implement neural networks to control processes in a wide region outside its training domain.
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