Tokni has developed a number of learning simulations for the purpose of understanding dynamic systems in a long term context, including:

  • OilSim, an upstream business simulation – acquired by Schlumberger in 2014
  • SeafoodSim, an ecosystem-based fisheries management simulation – developed in 2014-16 as part of Mareframe, an EU Framework Program 7 project
  • EmissionSim, an energy systems simulation – being developed as part of REEEM, an EU Horizon 2020 project

All of these learning simulations are deployed in workshops led by expert facilitators in a collaborative setting. Some of the main components of these managed learning experiences are:

  • Learning by doing: do first, then understand the theoretical foundations
  • Collaboration: participants work together in teams and together with other teams to get to the best solutions
  • Progressive elaboration: solve the easy challenges first before moving to the complex systems
  • Data-driven decision making: study and combine information from a variety of surveys and reports to decide what to do
  • No single best strategies: every simulation run is unique, and the key is to understand the dynamics between actors, actions and timing
  • Time-based feedback loop: participants make decisions, track the impact and how circumstances change, and adjust their decisions as time moves forward
  • Web-based: only need a standard browser to participate

Recently, Tokni has developed online decision support software for multi-criteria analysis and Bayesian belief networks, and has started combining these with the said learning simulation systems. This works both ways with the learning simulations being used as a vehicle for providing input for the decision support tool, and the decision support tool assisting users of the learning simulations in selecting the best strategies in a virtual setting.