This thesis presents a novel method of modelling metacognition computationally.
Metacognition is described as cognition acting on itself, and can improve memory, reasoning, emotional regulation, and motor skills. How it does this remains unclear. The two major barriers are: its high abstraction and disputed terminology.
To overcome these barriers this thesis employs a computational cognitive architecture to define the base units of cognition, and how they come to act on themselves. Well-defined computational units are built upon to form increasing complex metacognitive processes. These computational forms of metacognition are then connected to the research literature and built into working models in ACT-R.
The intention of this thesis is to help clarify the nature of metacognition and its underlying mechanisms.