Learning by generation in computer science education

• Main Author: Andreas Kerren
• Format: Article
• Language: English
• Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2004-08-01
• Series: Journal of Computer Science and Technology
• Subjects: finite automata; generation; explorative learning; visualization; animation; evaluation
• Online Access: https://journal.info.unlp.edu.ar/JCST/article/view/899

The use of generic and generative methods for the development and application of interactive educational software is a relatively unexplored area in industry and education. Advantages of generic and generative techniques are, among other things, the high degree of reusability of systems parts and the reduction of development costs. Furthermore, generative methods can be used for the development or realization of novel learning models. In this paper, we discuss such a learning model that propagates a new way of explorative learning in computer science education with the help of generators. A realization of this model represents the educational software GANIFA on the theory of generating finite automata from regular expressions. In addition to the educational system's description, we present an evaluation of this system.