Equipped with interactive simulations and acting as behavioural decision researchers, system dynamicists have established a typology of dynamic decision errors. Contrary to initial predictions from experimental economists and some decision scientists, findings of systematic deviations from optimal decision behaviours persist in dynamic and feedback rich environments. Pragmatic investigations into whether various training programs might help mitigate decision errors have provided some insights into the fact that subjects do not apply insights easily within or between dynamic decision tasks. – However, no comprehensive framework to help design of interactive learning environments that aim to mitigate decision weaknesses has resulted yet. In order to help formulate such a framework, this presentation reviews five different research streams: Static judgement and behavioural decision- making; Dynamic decision-making; Education and improvement; Problem solving and Higher level frameworks. Indeed rediscovering Forrester’s position that much data resides hidden in decision makers’ mental models, the review indicates that effective learning approaches in dynamic decision must adress both analytic and intuitive cognitive processes separate and in combination. Documented failures in achieving productive improved mental models is re-evaluated in this framework, and suggestions for further research outlined.