Machine learning class with automatic learning materials

Abstract

In this paper, an experimental class teaching Machine Learning such as Artificial Intelligence is presented. In this class, all teaching materials distributed to students are automatically processed with a set of XML compilers, after being inputted by the teachers with a GUI input tool. The compiler set was designed to generate three different forms of teaching materials from a single file using XML based semantics. Both students and teachers used all three forms in defined stages of learning process. The class activities and its teaching materials are refined by the toolkit in a highly systematic and organized manner, results, in the experimental class, with better initial understanding, less confusion, more active response and better class atmosphere. This leads to a better support form decision making.