Abstract: Simulation has proved to be a useful method to improve learning and increase the safety of work operations in several domains (healthcare, road safety, etc.), both for technical and non technical skills (NTS). However, the observation, assessment and feedback about these skills is particularly complex, because the process needs expert observers and the feedback is often provided in judgmental and ineffective ways during the post-simulation debriefing. In our research, we wanted to apply simulation to the electric domain as a new method to enhance the NTS and foster best practices. We developed and tested a set of observation and rating forms of the NTS behavioural markers of electric workers. In addition, we outlined the framework for observing behaviours based on non-verbal cues, like movement in the operational environment. The analysis of social signals and face-to-face communication patterns (e.g., kinesics, proxemics, interpersonal synchronization), could be combined with performance metrics (e.g., feedback on the NTS, self and peer assessment of performance efficiency, etc.). By automatically quantifying human behaviour using wearable and non-invasive sensors, we can find relationships between sensor data and team performance and thus identify optimal behaviour patterns that would lead to improved and safe performance.