Investigating how people understand the systems around them—from technology to democracy to our own bodies—is a common research goal across many disciplines. One of the practical aims is uncovering differences between how people think systems work and how they actually work (particularly where differences can cause problems) and then addressing them, either by trying to change people’s understanding or by changing the way people inter- act with systems so that this better matches people’s understanding [1].

Being able to say that you under- stand a system is essentially saying that you have a model of the system [2]. In HCI and other people-centered design fields, attempting to characterize people’s mental models of technology in which their behavior plays a role can be a significant part of user research. Users’ mental models will perhaps only rarely accord exactly with designers’ conceptual models of a system [3], but this is not necessarily a problem in itself: “[A]ll models are wrong, but some are useful” [4]. Mental models should not be assumed to be static constructs covering the whole of a system; multiple models working at different levels of abstraction can be relevant in different circumstances, from complex work domains to simple everyday interactions [5].