The COVID-19 crisis has demonstrated the importance of being able to understand complex computational models for everyday life. To make sense of the evolving predictive models of the COVID-19 pandemic, global citizens need to have a firm grasp of both systems thinking (ST) and computational thinking (CT). ST is the ability to understand a problem or phenomenon as a series of interconnected elements that produce emergent behaviors. CT involves decomposing a problem into quantifiable elements represented in an algorithmic form that can be interpreted or calculated by either a computer or a person. One new framework seeks to support student engagement in ST and CT by contextualizing these two types of thinking within the practice of constructing computational models. This framework explores how various aspects of ST and CT are embedded within different modeling practices, as well as how these modeling practices can help students as they construct, revise, and use computational models. This article explores how students interact with the various aspects of ST and CT as they build and refine computational models using SageModeler (a free web-based semi-quantitative system modeling application) in a chemistry unit on evaporative cooling. Through the examples presented in this article, the authors illustrate ways in which this framework can inform curriculum design and pedagogical practice.