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E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor.This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra's algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHS.

Many commercial or open-source systems for organizing courses are available, offering access to course materials, communication support, and receiving and grading student submissions. However, most of these systems are by default not ideally prepared to address specific demands of Computer Science (CS) education. We explore how Moodle as one of the most popular and free systems can be better adapted to support the needs of CS education and provide concrete guidance on features and extensions that could be explored. This report and work based on it can significantly improve courses for educators and students alike.

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