Is DeepSeek a Metacognitive AI?

The relationship between metacognition and DeepSeek models represents a compelling and yet underexplored area of research. Metacognition refers to a system's capacity to monitor and comprehend its own cognitive processes, which includes the active regulation and adjustment of its procedures. In the DeepSeek-R1 and DeepSeek-R1-Zero, it is evident that the interactions between the system's monitoring and control processes are both present and crucial for achieving the coherent and often surprising levels of reasoning that define these models. In particular, the "aha moment" is discussed as the best example of a sort of metacognitive behaviour in the DeepSeek models. In this sense, DeepSeek could be paving a new avenue for reasoning in Artificial Intelligence (AI) by prioritizing reinforcement learning (RL) over the more conventional approach of supervised fine-tuning (SFT). This study aims to analyse the implications of such innovations for machines' abilities to simulate behaviours based on self-reflection and to act accordingly. We will explore the extent to which these elements can be associated with metacognition, a trait traditionally considered to be uniquely human. Furthermore, from an educational standpoint, the significance of the relationship between advancements in DeepSeek and metacognition is highlighted, particularly in relation to the importance of prioritizing metacognitive approaches in education.