In master's thesis, we focus on algorithms that generate perfect mazes, the evaluation of the difficulty of the mazes, and the ranking of the algorithms according to the difficulty of the generated mazes. We explore the theoretical background of the selected algorithms: Prim's, Kruskal's, Hunt and Kill, Aldous-Broder, Depth-first search and Bacterial Growth. We create an interactive environment (application) for learning Prim's and Kruskal's algorithms for creating mazes. We evaluate the difficulty of the generated mazes using a Markov chain according to the average number of steps the program takes to find the path in the maze. We are interested in evaluating the suitability of an application for self-directed learning of selected maze generation algorithms, targeting students in the third educational cycle of primary school and the beginning of secondary school (ages 12-16). We test and evaluate the application with three opportunity-selected students. The master's thesis will contribute to the teaching of computer science with an application that will teach users new algorithms and allow them to create and evaluate mazes that they can use in introductory programming.
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