Teaching introductory artificial intelligence using a simple agent framework

This paper describes a flexible method of teaching introductory artificial intelligence (AI) using a novel, Java-implemented, simple agent framework developed specifically for the purposes of this course. Although numerous agent frameworks have been proposed in the vast body of literature, none of these available frameworks proved to be simple enough to be used by first-year students of computer science. Hence, the authors set out to create a novel framework that would be suitable for the aims of the course, for the level of computing skills of the intended group of students, and for the size of this group of students. The content of the introductory AI course in question is a set of assignments that requires the students to use intelligent agents and other AI techniques to monitor, filter, and retrieve relevant information from the World Wide Web. It represents, therefore, a synthesis of the traditional objectivist approach and a real-world-oriented, constructivist approach to teaching programming to novices. The main aim of implementing such a pedagogy was to engage the students in learning to which they personally relate while attaining intellectual rigor. Classroom experience indicates that students learn more effectively when the traditional objectivist approach is combined with a constructivist approach than when this orthodox approach to teaching programming to novices is used alone. Index Terms--Agent framework, artificial intelligence (AI) course, intelligent agents, introductory engineering course, Java, rule-based reasoning, semantic network, World Wide Web search.