Teaching AI Search Algorithms in a Web-Based Educational System

In this paper, we present a way of teaching AI search algorithms in a web-based adaptive educational system. Teaching is based on interactive examples and exercises. Interactive examples, which use visualized animations to present AI search algorithms in a step-by-step way with explanations, are used to make learning more attractive. Practice exercises, which are interactive exercises where immediate feedback is given when a student makes an error, but further help is optional, are also used. So, the student can try by him/herself to correct the error or ask for help from the system. Finally, the student can take a test consisting of assessment exercises, which are interactive, but no help is provided. The result of the test determines the student's knowledge level. Evaluation of the system through a pre-test/post-test and experimental/control group method gave very promising results about learning capabilities of the method. Also, results of a questionnaire show that the majority of the students liked the system very much. [For the full proceedings see ED562127.]