Adapting the Teaching of Computational Intelligence Techniques to Improve Learning Outcomes

Abstract

In the Master of Science program Business Information Systems at a Swiss university, the authors have been teaching artificial intelligence (AI) methods, in particularly computational intelligence (CI) methods, for about ten years. AI and CI require the ability and readiness of a deeper understanding of algorithms, which can hardly be achieved with classical didactic concepts. Therefore, the focus is on assignments that lead the students to develop new algorithms or modify existing ones, or make them suitable for new areas of applications. This article discusses certain teaching concepts, their changes over time and experiences that have been made with a focus on improving students’ learning outcomes in understanding and applying special AI/CI methods such as neural networks and evolutionary algorithms.