Self-Directed Learning in Adaptive Training Systems: A Plea for Shared Control

In the field of aviation, air traffic controllers must be able to adapt to and act upon continuing changes in a highly advanced technological work environ- ment. This position paper claims that explicit training of self-directed learning skills (i.e. the ability to: formulate own learning needs, set own learning goals, and identify learning tasks that help to achieve personal learning goals) is important for future professionals in aviation. In this paper, we present an adaptive training system in which the system and trainee share control over learning task selection and which can help trainees to develop their self- directed learning skills

Fostering self-regulation in training complex cognitive tasks

In complex cognitive domains such as air traffic control, professionals must be able to adapt to and act upon continuing changes in a highly advanced technological work environment. To function optimally in such an environment, the controllers must be able to regulate their learning. Although these regulation skills should be part of their training, this is not usually the case. This study evaluates a training program that integrates air traffic control skills with regulation skills. The participants were 29 air traffic control students who followed either the original training program (n = 12) or a new program (n = 17) in which the development of regulation skills was embedded in the training of domain specific skills. Compared to students in the original program, the students in the new program showed increased self-efficacy in the use of self-regulated learning skills with improved performance in domain specific competences. The implications of these findings are discussed with regard to the daily training practice of complex cognitive skills