This project aims to serve the national interest by improving curricula in computer science education. Computing professionals need to understand the possibilities and limitations of computation in order to design efficient algorithms for problems that can be solved in practice, or to avoid large investments in attempts to implement solutions for problems which have been proven to require unreasonable amounts of time or other resources. Modeling computation is an important building block for this understanding, however, students often struggle with abstract modeling and visualization. A prior Level 1 Engaged Student Learning project resulted in a prototype tool which provides immediate feedback on the computational models designed by students. This Level 2 Engaged Student Learning project aims to add features to the tool, improve its usability and adaptability, and investigate its impact on student problem-solving at a larger scale, in different educational settings. The existing Automated Feedback for Computing Theory (AFCT) prototype tool was built on the widely used Java Formal Languages and Automata Package (JFLAP) visualization tool that aids students in learning the basic concepts of formal languages and automata theory. The enhanced tool developed in this project will initially be deployed and outcomes assessed in theoretical computer science courses at the five collaborating institutions. It will be made available under an opensource license to enable others to use