AI-Assisted Learning

AI-Assisted Learning and Cognition

Large language models and adaptive tutoring systems offer promising new ways to enhance learning. We explore how personalised AI feedback can correct misconceptions, deepen understanding, and produce lasting changes in knowledge and beliefs. Our work examines AI-driven dialogue in educational settings—its potential to improve learning, and its implications for critical thinking in an increasingly AI-driven world.

Cognitive Biases

Cognitive Biases and Decision-Making

We study the cognitive biases that shape judgment across domains—from visual biases in forensic science to everyday reasoning errors. Our fingerprint research revealed how contextual information can influence even expert decision-making, challenging assumptions about objectivity. We're now investigating how expertise and cognitive strategies can help overcome biases in areas like financial forecasting, medical diagnosis, and public policy.

Insight

Insight Experiences and Belief Formation

We're building a framework to study "Aha!" moments—those sudden realisations that shift understanding and shape beliefs. Expanding on the Eureka heuristic, we examine the depth, "mystical" qualities, and ineffability of insight experiences. We're particularly interested in how these sudden revelations influence beliefs about conspiracy theories and paranormal phenomena, and how understanding these processes can promote critical thinking.

Resilience

Resilience in High-Stakes Professions

In collaboration with the Queensland Police Service and Queensland Ambulance Service, we study how forensic investigators and first responders maintain well-being despite frequent exposure to traumatic events. Through qualitative interviews, cognitive tasks, and physiological measures, we're identifying the traits and strategies that contribute to resilience—with implications for recruitment, training, and support in high-stress fields.

Publications