We developed a web-based tool for learning the order of evaluating expressions in C++ and Python languages. The variety of operator precedence and associativity among programming languages and the lack of direct visualization make understanding expression evaluation difficult for some students. The key feature of the new system is a detailed explanation of errors, containing fault reasons---the subject domain laws that the student violated. We evaluated the tool with 14 first-year Computer Science students and received positive feedback. This tool can be used for learning new concepts during homework without requiring more class time because it provides enough feedback for students to learn on their own.

Developing an understanding of control structures is one of the important tasks in introductory programming courses. To facilitate active learning with immediate feedback, we developed a constraint-based tutor, "How it Works: Algorithms," that asks students to build an execution trace of the given algorithm and provides explanatory feedback about the mistakes the student made. The reasons for the student's faults are determined by an inference engine, using a set of rules describing the subject domain. Teachers can create exercises using a simple visual block-based interface and sending them to students as permanent links.

One of the ways to demonstrate subject-domain concepts is to let the learner play in the domain-related sandbox, while receiving the explanations of the domain laws that were broken when the user makes a wrong move. This can help the learners who understand definitions of the concepts poorly. We present two visual simulators for demonstrating concept properties and domain laws, implemented as web applications. They can be used to study programming, enabling trial-and-error learning, supported by the error messages, explaining why the user's action was wrong.