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A lot of working environments today show characteristics of complex socio-technical systems, consisting out of complex physical-technical systems and networks of interdependent actors (De Bruijn & Herder, 2009). These systems are characterized as increasingly interconnected, and their infrastructures composed of different technological layers inter-operate within the social component that drives their use and development (Vespignani, 2012). For example, a container terminal can be defined as a complex socio-technical system, being an important node in the worldwide transportation network, connecting different modalities of transportation and storing goods (Saanen, 2004). Related to these characteristics, the planning of operations in a container terminal is complex, dynamic and interdependent. Operations that have to be planned are e.g. the location and time of an arriving vessel, the loading and unloading of the vessel, and the further storing or transportation of the goods from the vessel. Current planning practice involves a decomposition of single planning tasks, conducting them in a sequential manner. This approach leads to sub-optimal results, while the container industry is highly competitive, and time, money and quantity of goods handled play an important role (Zeng & Yang, 2009). Such dynamic, complex, and technology dependent work environment requires employees with adaptive skills (Penney, David, & Witt, 2011), characterized by the ability to handle dynamic situations, to deal with stressful events, to manage crisis situations, and to navigate unfamiliar or unpredictable work situations (Pulakos, Arad, & Donovan, 2000). Furthermore, it requires a holistic understanding of what is going on within the container terminal, called situational awareness (SA) (Endsley, 1995). SA and multi-stakeholder decision situations (confronted with time restrictions and incomplete information such as emergencies) have been recognised as a relevant field for specific training approaches involving tabletop exercises (Dowell & Hoc, 1995), non-computerized tactical decision training games (Crichton et al., 2000), or multi-user mobile games for shared decision training (Klemke et al., 2014). In our study, we introduce a novel approach to learning in complex socio-technical systems called microgaming. We show how one microgame is used to support the development of SA of the actors involved in a complex system, and how this could influence planning task performance. In the following section, we briefly illustrate why SA is important for actors in complex, socio-technical systems, before we introduce our concept of microgames. In the fourth section, we represent our study with a microgame, before we end up with a discussion and conclusions.