Computational models are increasingly at the center of public discourse on topics ranging from investment strategies to climate change. How can we help our students understand the basic structure, strengths, and limitations of such models? Computational models in introductory physics are not complex mathematically, and can produce rich and surprising behavior in simple model systems. Integrating simple computational modeling into the university-level introductory physics course can help students gain a deeper understanding of the functioning of fundamental physics principles, as well as allowing them to explore the effect of parameters such as step size which are important in many classes of computational models. Appropriate tools allow even novice programmers to concentrate on the physics and mathematics of models rather than on the complexities of coding. One example of such a tool is VPython (http://vpython.org), which produces dynamic 3D animations of objects and their motion without requiring any graphics or interface coding. I will show examples of computational activities which we have integrated into the introductory calculus-based physics course taken by science and engineering students, and will discuss ongoing research directed at improving these activities.