Augmenting behavior-modeling training: Testing the effects of pre- and post-training interventions
A number of recent training authors have suggested that pre- and post-training interventions may enhance training outcomes. In the present study, pre- and post-training interventions were added to an established behavior-modeling program on assertiveness, creating four conditions: (1) no intervention, (2) pretraining interventions, (3) post-training interventions, and (4) both. One hundred fifty trainees completed the module, and measures of trainee reaction, learning retention, and behavioral change were obtained. Results indicated that the post-training intervention strongly affected learning retention, as well as reactions immediately following training, with moderate effects on behavior. No significant effects were observed between the pretraining intervention and any of the trainee outcome measures. Implications of the findings for training research and practice are discussed.
Flexibility of Cyber Physical Production Systems (CPPS) has already been widely discussed, but apart from some definitions, only few measures exist. These, however, are required to compare different CPPS regarding their flexibility and the effort necessary to increase flexibility during evolution. This paper presents the application and evaluation of already proposed flexibility and adaptivity metrics for automated Production Systems. The interdependencies among product, process and resource are shown. An AML description is provided for a lab size application example as a basis to demonstrate changes that incorporate flexibility. Such changes are to produce heavier work pieces (WPs), realize different processes and use different resources. At the example of the model in Automation Markup Language (AML), we highlight the interdependencies between product, process and resource, thus showing the strengths and weaknesses of the proposed metric.