A Second-Order Adaptive Network Model for Organizational Learning and Usage of Mental Models for a Team of Match Officials

This paper describes a multi-level adaptive network model for mental processes making use of shared mental models in the context of organizational learning in team-related performances. The paper describes the value of using shared mental models to illustrate the concept of organizational learning, and factors that influence team performances by using the analogy of a team of match officials during a game of football and show their behavior in a simulation of the shared mental model. The paper discusses potential elaborations of the different studied concepts, as well as implications of the paper in the domain of teamwork and team performance, and in terms of organizational learning.</p

Computational Analysis and Simulation of Organisational Learning

Joint Keynote Speech. Organisational learning emerges as a cyclic interplay of various mechanisms at different levels. To analyse and simulate organisational learning computationally, the self-modeling network modelling approach from AI provides a powerful means to address the complexity of the interaction of different mechanisms and the control over them. In this keynote speech, recent developments are presented showing how this approach can be used to analyse and simulate complex processes of organisational learning. This covers both feed-forward learning to learn shared team or organisation mental models out of individually learned personal mental models and feedback learning to let individuals learn personal mental models from shared mental models. It is shown how by a self-modeling network, the different types of learning can be modeled using a first-order self-model for the learning and a second-order self-model level for the control over the learning. It will be discussed how this may be applied in the context of improving safety in health-related organisations such as hospitals