In this lecture, we cover topics related to Chapter 10 of Morecroft (2015) on model validity, mental models, and learning. We revisit the general description of a model and discuss how models can range from analogue to metaphorical, with "illustrative models" balancing the two and providing plausible scaling with generalizable insights. The discussion guided by Morecroft (2015) is interleaved with classic arguments from Frank Keil about the shallows of explanation and illusions of depth. We discuss how formal models are "transitional objects" that allow for deepening the understanding of mental models as well as joining with others in collective cognition and cognitive division of labor. We close the discussion with examples of how to build confidence in mental models through verifying correct boundaries, structure, and calibrated parameter values. Significant confidence in a validated model comes from learning something new about the system being modeled.
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