Metacognitive Threshold

Metacognitive threshold research explores the minimum stimulus needed for conscious awareness of a mental state, aiming to understand and improve its regulation. Current investigations focus on computational modeling of this threshold, employing techniques like deep reinforcement learning to create adaptive interventions that enhance metacognitive skills, particularly in educational settings and human-AI collaboration. This work has significant implications for improving learning outcomes through personalized instruction and optimizing human-AI teamwork by addressing biases in self-assessment and reliance on AI systems.