Learners' (mis)understanding of important and difficult concepts: a challenge to smart machines in education

By Paul J. Feltovich, R. L. Coulson, R. Spiro. 2001

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Metrics for Explainable AI: Challenges and Prospects (2018, background): “An insight can be thought of as the self-awareness of a "knowledge shield" (Feltovich, Coulson, and Spiro, 2001).”
Adaptive Skill as the Conditio Sine Qua Non of Expertise (2018, background): “It is on this point that D/F and CFT converge: The tendency to fixate on and attempt to preserve the initial account or frame in a cognitively rigid manner, using knowledge shields to explain away or ignore contradictory data (see Feltovich et al., 2001).”
Fish Swim, Rocks Sit, and Lungs Breathe: Expert-Novice Understanding of Complex Systems (2007, background): “Multicomponent phenomena that are invisible, dynamic, and interdependent are particularly difficult to understand (Feltovich et al., 2001; Feltovich, Coulson, Spiro, & Dawson-Saunders, 1992).”
What Do We Want From Explainable Artificial Intelligence (XAI)? - A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research (2021, background): “Examining understanding of software has a long history in human-computer interaction and education [108, 153].”