visualisation of topological structures as a training tool for acquiring causal models of complex systems
Motivation -- Our research aims at developing and investigating training strategies that foster the development of causal models of complex systems. Research approach -- An experimental approach was used in which 90 students were trained in handling a simulation of a process control system. Training tools differed regarding the type of visualisation of process components and the extent of learner control. Causal model quality was assessed through both a knowledge questionnaire and the performance in a regulation task with the process control system. Findings/Design -- Results indicate an influence of visualisation and training strategy type on quality of system knowledge but no effects on performance in system interaction. Take away message -- A visualisation of process interrelations in combination with a learner-controlled training mode leads to adequate knowledge acquisition.
causal models training strategies visualisation tools