Computer science education has been at the heart of Scheme from the beginning. The language was designed in the 1970s concurrently with the MIT course 6.001 and the textbook “Structure and Interpretation of Computer Programs” (SICP). To explain the scope of variables at run time in the presence of higher-order procedures, SICP introduces a mental model called the environment model, along with a pictorial representation of environments and data structures. Recently, the concept of notional machines has emerged in computer science education: a predictive set of abstractions that define the structure and behavior of a computational device. Proponents of notional machines argue that learners benefit when complex dynamic concepts such as the computational structure of Scheme are accompanied with concise notional machines. In this paper, we start with a sublanguage of Scheme sufficient for all programs in SICP that we call SICP Scheme. We extend the environment model to a full notional machine for SICP Scheme that is simple enough to serve as the central mental model in a CS1 course and demonstrate the machine with computer-generated visualizations. Moving beyond SICP Scheme, we show how the notional machine can be further extended to explain Scheme’s call/cc and thus make this powerful concept accessible to beginners through a coherent mental model. The presented notional machine serves as the core of a web-based implementation of Scheme that is under development at our university.