When developing automated assessments and intelligent tutoring systems, a lot of routine effort goes into developing the bank of learning problems. Problem generation is the way to automate this process. In this paper, we present a method of generating expression-related problems for teaching introductory programming courses. The problems are generated from open-source software code which allows keeping learning problems similar to the production code the students should learn to analyze and write. Generated problems are automatically classified by their difficulties and the knowledge they need to solve, represented as sets of possible errors. This allows seamless integration with adaptive learning algorithms. The evaluation showed that the generated problems are indistinguishable from human-authored problems and suitable for use in the educational process.

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.