Measuring and modelling how people learn how to plan and how people adapt their planning strategies to the structure of the environment

Often we find ourselves in unknown situations where we have to make a decision based on reasoning upon experiences. However, it is still unclear how people choose which pieces of information to take into account to achieve well-informed decisions. Answering this question requires an understanding of human metacognitive learning, that is how do people learn how to think. In this study, we focus on a special kind of metacognitive learning, namely how people learn how to plan and how their mechanisms of metacognitive learning adapt the planning strategies to the structures of the environment. We first measured people's adaptation to different environments via a process-tracing paradigm that externalises planning. Then we introduced and fitted novel metacognitive reinforcement learning algorithms to model the underlying learning mechanisms, which enabled us insights into the learning behaviour. Model-based analysis suggested two sources of maladaptation: no learning and reluctance to explore new alternatives.